Name: SolarWinds Observability SaaS Product Update (Q3 2026)
Uploaded: 2026-09-30T16:30:31.824Z
Duration: 58 min 8 s
Description: SolarWinds Observability SaaS Product Update (Q3 2026)

Transcript for "SolarWinds Observability SaaS Product Update (Q3 2026)": Hey, everyone. Good morning, good evening, and good afternoon based on wherever you guys are based off. We'll be starting, the session in a minute just to accommodate, users who are joining a little late. So, yeah, stay tuned for probably thirty nine thirty seconds from now. Ten more seconds, guys. Alright. Here we go. Hey, everyone. Warm welcome to you all for our third edition of the SolarWinds SaaS product update webinar. As always, we are super excited to have you all with us today. Thanks for joining. Firstly, thanks again to everyone who joined us during the previous editions and shared your valuable feedback and questions and also the ideas. Those have been very insightful for us and a great inspiration to run this program every quarter. With this quarterly series of webinars, we intend to have an ongoing conversation about our product innovation and the capabilities that matter you the most. As you may know from previous webinars, I'm Pramod from the product marketing team here at SolarWinds, and I'm joined today by an incredible team of our product experts. Before we begin, a few housekeeping notes for today's session. I know it's boring for you guys. But, yeah, all attendees will remain muted muted throughout the webinar today. You can interact with us using the chat panel, and please use q and a tab to submit your questions during the session. We'll do our best to address as many questions as possible in today's session and also during the live q and a segment at the end. As a part of today's presentation, we may discuss some forward looking statements related to our future product capabilities, road map items, and also the strategic direction. These represent our current plans and expectations, and they are subjected to change as we continue to evolve and innovate along with you guys. With that, let's move to our agenda. Here it is. We'll begin with our q three twenty twenty six retrospective. Tony will take us through the key milestones and the major deliveries of this quarter across all the modules of the SolarWinds Observatory SaaS. Post that, Tony will also take us through the focus areas of q four and will provide a glimpse at our product road map. We'll then move into our exciting part of today's session, which is platform in action, where we will showcase the top rated use cases that we have delivered in this quarter. As a highlighting thing of today, all of these features will be presented to you and also demonstrated to you by the product managers themselves who have worked exclusively on their respective features. After that, my colleague Sydney will take you through our numerous initiatives across my across marketplace, community, and events, and will also provide key information on our upcoming SolarWinds Day. With that said, I will hand it over to Tony to take it ahead. Tony, over, to you. Ramod. Thanks, everyone. Thanks again for taking the time to to join and, great to see a lot of familiar names here. Some of you who we've met recently at the various World Tour events. This is really a tremendous opportunity to, engage with you and gather your feedback, but also to show you the the work that the team have been working on over q three and give you an insight into, our q four plans. So we'll start with a a quick look, across, the quarter three retrospective in terms of, what we've done. But I think it's always worthwhile just to set the the context for why we do what we do, and that is defined within our product vision. The automation, the observability, the visualization, and remediation are the the key pillars, to delivering the facets of a true observability platform, all powered by SolarWinds observability and our AI platform. So our goal really is to achieve three outcomes for our customers, and that are they are unified visibility, proactive monitoring, and building towards that automated remediation. And I'm sure those themes will resonate across the q three retrospective and into q four as we look at more specifics in terms of what we've delivered and what we continue to invest in, on our SaaS platform. So a quick look at the delivery highlights, across the first four pillars of network infrastructure, reporting, and, of course, AI being a significant part of, all software development and, user facing interactions these days. Well, let's start with the network and the the core capabilities for configuration management. We've continued to build on the foundation that we've developed over the past twelve months to, enable bulk configurations, and improve that signature validation, and more configurability with exclusion rules within the device configuration management capabilities. Alerting and visibility, of course, are are key once devices are onboarded, ensuring that you have rapid access to, the right types of alert definitions. And so we've spent time investing into, alerting use cases reported by both our partner community and, customers to to drive that better visibility, across access points, switch stacks, and wireless controllers. One key feature that, I'm very proud of the team for delivering in terms of topology and and flow maps, continuing on that visibility with VPC logs and Sankey charts. We've also now introduced a a geo map for global, traffic tracking. That's a a really powerful experience when it comes to just a rapid visualization of where my traffic is leaving, what type of traffic is flowing through my network, and that kind of global view of what's happening east west and north south with traffic, powered by NetFlow. Within the network, pillar as well, we've also increased our support for devices, for FortiManager, improved the visibility into SD WAN tunnels and edge visibility, and also work to improve the the scalability as we're seeing really large scale adoption of SD WAN devices within customer environments now reaching in excess of hundreds of devices. And ensuring that our platforms can scale and meet that need is critical to the basic network needs of customers. The infrastructure area, tremendously exciting. I'm really, really encouraged by the developments I'm seeing with our Kubernetes, GitOps, developments, our entry into CICD and, the more modern way of deploying not just applications but infrastructure as a code, and looking to those cloud platforms to to bring more visibility into, into infrastructure. That is extended into, agent management. So simplifying the the fleet management within the platform, allowing customers to schedule those recurring agent upgrades using tags, tags being, what we see as a fundamental experience on the platform allowing you to manage entities, to find tags, which leads into alerts, reports, dashboards, and and other area. And we also do continue to extend our cloud and API monitoring. Again, just calling out that VPC flow logs and geo maps. There's probably far too much here, in terms of the time allocated to talk to all of these to you in any great detail. But if there's anything in particular that you see here across our recent releases, please feel free to to connect with us or ask a question in the chat, and we'd be delighted to to show you these in in more detail. Security and hardware, in terms of Kubernetes and, identifying API keys and tokens and that and those exposed secrets, through that Trivy integration that we've developed broadens the overall, DevOps and GitOps and infrastructure as a code use cases that you can achieve within that SaaS platform. One of the really high value call outs here on reporting visibility has been the release of a a a long anticipated feature. I think this is something we've spoken to customers in the self hosted platform, about for a number of years, and that is defining SLOs, SLIs, and error budgets. How how do our customers who manage services spanning on prem and SaaS platforms comprising of network and applications and database and websites? How do they build a a service delivery view, ensuring that, it's very easy to report upwards on service availability, tracking that error budget, and looking at adhering to any kind of compliance standards, or any internal, SLOs that might be defined for that service delivery. And this represents a a real significant milestone for us in terms of that delivery, that capability being released, exclusive to the the SaaS platform and really just broadening the the value that, is on offer with our SaaS, platform. We've continued to improve the widget and dashboard customization, improving that configuration experience, extending the number of rows within tables, and just those small quality of life improvements that that we hear from customers that, really just help, improve the day to day operational workflows when creating, widgets and, dashboards. Of course, our our APM story continues to evolve, in parallel with our goals for OpenTelemetry and deeper, instrumentation of applications and leads us into that LLM observability under the the AI pillar. But we have, improved the health summaries within APM, and added that aggregate KPI toolbar for trace views. And within AI, and I'm sure we could probably spend the entire hour talking about all of the AI use cases that we have delivered, our goals and objectives, especially for those, who attended the world tour, and got a glimpse into the future of, our agentic and gold AI strategy across the self hosted and SaaS platforms. But, individually, we continue to make investments into AI, particularly in the AI Query Assist, which is a a a truly valuable use case for optimizing SQL queries. LMM observability as a whole, understanding how our customers can get visibility into things like Vertex AI, context, queries, and, token usage and spend. They form part of our overall strategy not just to use AI, but to make AI observable for customers as they develop and consume those applications. Our cross platform assist or SW one, I'm sure some of you probably know the the name that's coming for SW one, but, those conversational or natural natural language interactions, We continue to extend the the data that's available, to our AI platform in order to provide broader coverage and that kind of cross platform, integration, which is central to our portfolio strategy, not just for observability, but encompassing other platforms and products within the SolarWinds portfolio to really give you that central experience of, connecting, all of the the data. So few other areas in terms of, recently released, and I've just gone over time, but I'll try and wrap up the the next two slides as quickly as possible. Database, digital experience, APM and logs, of course, part of our SaaS platform continue to receive, investment again based on that customer and partner feedback, unlocking use cases for better deadlock analysis, SQL Server blocking, profiler event tagging. All of these very domain specific for those who live in the the database realm. These are, you know, features that we develop based on that feedback of users who are troubleshooting and diagnosing complex SQL performance issues. Digital experience, again, continue to receive, improvements in reporting. There's quite a lot of development in terms of onboarding, websites, performing real user monitoring within our digital experience offer. The reporting aspect continues to drive most of the requests. Through previous developments, we released the public status website. Now we're continuing to invest into additional reporting. Perhaps one of the the more interesting areas, particularly within the SaaS platform, you know, traditionally, those of us familiar with the the self hosted platform would not have had exposure to the more modern ways of instrumenting applications using open telemetry, doing direct, or database trace integration. These areas really, expand the the capabilities of observability into the the more complex systems that customers are consuming, and are developing, their services towards. And so our OTAN story continues to receive that, that additional investment, which blends slightly into logs, as we look at, OpenTelemetry and application performance metrics, for spans, traces, logs, events. And as as that industry, continues to evolve and introduces new challenges for us, we react to those by extending our our logging capability with, Windows OTEL integration, log flow detection, and analytics into the the log profiles and log sources that are consuming, those entitlements on the SaaS platform. So looking ahead, quite a lot of exciting things delivered in q three, but still a long way to go. Rather than talk about the specifics of what's coming, we've generalized these into the the focus areas. They're going to to cover six different areas, greater coverage, so continuing expansion into multi cloud environments. We continue to receive feedback from customers about, GCP, AWS, and Azure services that are supported out of the box. So eliminating that need to use the API monitor, eliminating the need to use any custom scripting, and making that onboarding experience far easier, ensuring that we have that breadth and depth, of coverage. One of the exciting capabilities that's currently in preview and which Adrian is going to speak about shortly is the lightweight collector. This offers a a broader coverage in terms of, reducing TCO. Same types of network device coverage, but not to to to give you too much of a a read ahead, but, lightweight collector is a a a significant milestone in terms of our architecture to help customers reduce TCO. We'll continue investing into smarter solutions. I mentioned those goal oriented agents, that AI quick AI assisted query capabilities, alert correlation, and, enhancing anomaly detection, all of those pillars for smarter solutions revolve around our strategy to centralize AI capabilities, not just on the SaaS platform, but by encompassing other products within the the portfolio. They lead, of course, into that improved experience. So some of the areas that we're working towards, are improving topology and maps, introducing the notification center. We're also working on perhaps a a preview of a mobile app, which I'm sure many of you would be very interested in evaluating, as soon as available. So bringing all those, experience needs, not individual product capabilities, but that platform experience, and improving that across, q four are central to our our focus areas. So I touched briefly on kind of expanding that, multi cloud, those multi cloud capabilities. Adrian is gonna speak to you about the lightweight collector. AI and automation, of course, forms a key tenant. Ajit is going to to speak to us a little bit about, LLM observability. And we also are deepening, of course, our application and infrastructure visibility continuing, on that, journey to support on prem cloud, multi cloud platforms, providing the breadth and depth of capabilities that customers want, and also in parallel, making sure that we have a a powerful experience, for you. So, without further ado, I shall, leave the stage and, hand over to Pramod. Thank you all. Sorry. Sorry, guys. I'm sorry. Sorry, guys. So, yeah, before we get down to platform in the action section, we have a small poll in front of you. This is to steer our direction in in terms of the AI capabilities that we are developing as a part of our product portfolio. So, we will have this poll, live for next few seconds, and, then we will move into our next section. Okay. Few more seconds for polling. There you go. I have Ajit Raul, with me on the stage who will be taking us, with the next section. Ajit, over to you. Thank you, Pramod. Thank you, everyone, for joining. I'll, take few seconds to save my screen, and then I'll get started from there. Yeah. While Ajit, share his screen, he is a product manager, who is with SolarWinds with four plus years, and he's taking care of SOSAS, exclusively right now. So, Adi, over to you. Okay. So, today, we're going to focus on couple of features that we, kind of delivered in last quarter. Those are mostly related to our cloud observability, and SOW SaaS. And, these are the features that kind of tackles around three questions that every cloud, platform team asks, whenever they use a observability platform. Like, why, did something breaks, and, what is it costing me from a cloud or upload perspective? And, if, my cloud workload, is healthy or not or if my AI workload is healthy or not and performing well or not. So I'll start with, AI assist for cloud resources. So how, so SaaS generates an AI driven root cause narrative for cloud resources in seconds, instead of using manual trials, across different dashboards. Right? And, then I'll move to Azure cost observability, bringing Azure cost spend directly into source SaaS. So cost, telemetry sits next to your performance telemetry that you are already using without any kind of, context switching over Azure portal to your, SOA performance, telemetry. And then, we'll kind of talk about, the LLM observability piece of it, how we are extending our, observability platform to support LLM workloads, around, Azure OpenAI, AWS, Bedrock, Google Vertex AI, and, using those, how we can stop being, you know, stopping in a black box and, have been sighted into your performance telemetry, for all of your LLM, workloads. So I'll, just jump into the live demo from here. I'll start with AI assist for cloud resources. I believe my screen is visible. So, every SRE knows the pain, of an EC two instance, when it fires an alert, at 2AM in the night. And, that could be because of, your CPU is pegged and the on call engineer who has to manually, you know, pivot across, different telemetries, your metrics, logs, recent deployments just to form a hypothesis around it, for the first ten minutes of every incident and, you know, doing a pure, manual correlation between, different telemetries that, is being monitored. A assist, for, cloud resources kind of breezes that particular gap and, removes all manual hard drive steps. It kind of, have context into all of your metrics, logs, your recent changes, and, related entities, for your cloud resources and generates a structured root cause narrative, and remediation and recommendation on demand when, your cloud resources, are not performing well. So this helps in cutting the time to first hypothesis and, from minutes to seconds and helps you to kind of get to the root cause immediately and, also helps you with, the next steps, so that, with no time, you can take actions, and, you know, resolve that particular incident. So there are two ways how you can do this. You can kind of look into a specific cloud resource. If that cloud resource is not doing well, you can just, trigger, the investigate from here. That will kind of open the assist for you, providing you all the summaries of, that particular problem and, then the root cause of it. Or, you can kind of jump into a particular entity and just, click on this SW one and simply ask why my entity encountered with some unexpected spikes, what caused this particular, spike. And then, this ASIS, kind of gives you a reach, summary starting with the verdict of what went wrong and when it went wrong, and then the current health state, the exact root cause of, it, so you can get your findings, from all of your telemetry that you are kind of, collecting right now. And what all breaches happened around that time if, any alerts are fired for a related entity or the same entity. And, then it also looks into your logs. Like, if there any, there there are any evidences in your logs causing, some sort of, you know, problem to, your specific entity, then, it, saves the detailed observations around what went wrong, when it went wrong, and, what all things are getting impacting because of that. And then, the next steps, like, what all actions you can take, for it to kind of, immediately fix that particular incident and kind of, bring your, entity, to a healthy state from a unhealthy or, bad health state. So that's how, this AI, assist for cloud resources helps, you to kind of reduce, your mean time to detect, and mean time to resolution, from minutes, to seconds with, a few clicks. And, this is something we started, supporting with, AWS CC two. Then we extended it to all compute services, across AWS, GCP, and Azure. Then, we are we also extended this to, different category of services like your API gateways, database, services. So this root cause summary that I'm kind of currently showing you for a Azure cosmos DB, entity, which is a database, entity. With this, I'll, jump onto the next, feature that is our, cost observability piece. When DevOps and platform teams already lives inside, so to kind of, monitor their performance telemetries, regularly checking in for their performance states, health soft their, current monitored entities, to kind of ensure the performance and reliability is there for their platform. But when a deployment or or misconfiguration causes, some, cost spike on your Azure, spend, that visibility, is kind of missing earlier. They have zero visibility into it, from in inside the tool. But today, like, they they have to kind of context switch between the Azure cost explorer and, so to kind of correlate, these two, telemetry is that when something goes wrong, the cost, goes up, and, they need to kind of look into it in bits and pieces and, kind of do, swell sharing, between two consoles to answer. And did any deployment or any misconfiguration blow up, our bill or cost? So that's where, our, cost observability comes into the picture, which, brings, the spend visibility directly into so so cost, sits next to the, health and performance telemetry team is already using to troubleshoot any, performance issues, right now. This is, the cost of stability dashboard where we kind of, track all, cost related telemetries starting with your month to date spends across your accounts, cloud resources, and individual resources. And, you also get visibility into your monthly spends, top accounts, by spend, spend by specific services, like, for example, you are using, some virtual machines, that virtual machine category could be, you know, contributing, to your cost at a very, high margin, and there could be some small service categories that could be kind of, having low cost. So you can kind of look into that particular information by, having this, service level category, and, you can kind of go into specific category to look into compute level details, networking level, details, into the cost. And, also, we also bring in, the cost, for, the current trend versus the forecast. You can kind of understand what is your current cost look like and, how your forecast looks like. Along with that, we also provide, you know, account label, details into your cost. You can go into a specific account, to kind of analyze, cost for a specific account and, look into the details of, individual resources in that particular account. And, if you have any AI work workloads running in your, account, you can also look into that, at the call a cost tab, or you can just simply, filter that particular, service and look into, those a a workload costs. So, this is something, we are kind of, building. We'll continue to build, towards it, and we'll bring in more features that will help customers, in analyzing cost and correlating cost with different, performance telemetries. Those will be coming in upcoming, releases. I'll move on to the next topic from here, and that is LLM observability piece, where, we are kind of bringing in AI, observability. Basically, the platform level observability, of LLM, to supporting Azure OpenAI entities as a first class entity, AWS bedrock, and, Google Vertex entities as first class entities in source Us currently. As you open AI, Bedrock and, Google Vertex AI, so if, a customer is having any kind of, generative AI models, into this stack, and, they are using any of these services, and, then they immediately loses the visibility, at the moment. The request their request leaves their own, application service. And, if, you want to ask, a question, like, is a slow chatbot response, because of the model is being slow or, the retrieval step, or is is my, month's, AI bill is spiking because of more traffic or some inefficient prompts? So these all questions are kind of, very much, open ended without having LLM observability. Teams are kind of, flying blind without, these, observability, signals, both on the reliability, side and, on the cost side of the AGO workloads currently. LMM observability extends, towards existing, cloud and APM telemetry into, the model layer by surfacing your invocation counts, latency, error rates, and, your token uses related telemetries, for all of your cloud resources across your AWS bedrock as your open AI and, the vertex AI entities. So, currently, you can kind of monitor these workloads as first class entities. I'll kind of talk through, the platform side of it, the infrastructure side of it, then I'll, let Samek jump in, from to kind of talk about the APM side of it, how we can kind of, do monitoring on the traces and, everything. So I'll start with, then, bedrock entity, how we kind of support bedrock entity. We kind of collect invocations related metrics, the invocation latencies, errors, token counts, then, time to first token. So all of these, metrics are collected. So you get a, out of the box visibility into these metrics. Along with that, we have couple of additional metrics as well, using which you can create custom dashboards. If you are ingesting logs into the platform, you can also have visibility into the logs from here itself, of your AWS bedrock, cloud workload. Similarly, we have, Azure OpenAI, we kind of collect a bunch of metrics around Azure OpenAI, around requests, completion tokens, in inference tokens, availability rate, time to last byte, and all of those metrics are collected as part of our OpenAI service. And there are a bunch of other metrics that are also there for our Azure OpenAI service, which you can, use to monitor, set an alert, or build a custom dashboard around it based on your own need and use case. I'll jump on to couple of, vertex AI entities. We support around eight entities as part of our vertex AI. So the entities around, Firebase site hosting, deployment resource tool, a endpoint, featured online store, feature store, a index, pipeline jobs, publisher model. So all of those entities we support as part of, Vertex AI. So I'll go through just couple of entities, over here. I'll and, so you but all metrics we kind of collect as part of those entities. We kind of collect, the resource utilization, replicas, for our a index endpoint, and then the site related information, the memory related informations. There are bunch of other metrics that are also present which can be used for alerting and custom dashboards. Similarly, for, other, services we collect, all of those metrics that are exposed by, our, Google, platform API currently. And, those metrics, can be, you know, used for alerting, visualization, and, custom dashboards in our source. And, using those, you can have a better visibility into, your LLM models, platform level layer and understand how, those, resources are performing. If there are any problems, you can kind of look into them, try as them. And with this, I'll kind of, hand hand it over to Samek and up to talk through, the LLM, tracing, how we kind of monitor, the LLM applications and do the, tracing of it. Hello, everyone. So as, Arit mentioned, the other part of the LLM observability is the ability to, monitor the LLM related, workflows from the perspective of instrumented applications. So if in your eight eight, if you if in your or yeah. In your if you if in your services portfolio, you have, services which are using LLM engines. Right now, it's much easier to monitor their LLM activities using, SWOT APM. So the first, level of the monitoring is the very high level. We prepared a dedicated dashboard, which can be found in the dashboard in the predefined dashboard list. It's called LLM, overview. And in this dashboard, we are displaying aggregated information, related to LLM, operations which are performed by the services. So we can see all the total number of the LLM calls, the average call duration, the total number of consumed, tokens, and also the information about number of services, instrumented services, which are performing LLM operations, number of providers which are used, and number of models which are used. You can also see some time related statistics to the LLM calls and usage. And on the bottom of the dashboard, we have a list of the services which are actually, utilizing LLM capabilities. So as you can see in my, in my my demo environment, we have one service, which is which is utilizing LLM, engines. And in the service details itself, for now, there is there is no changes, but we also introduced information related to the LLM to the trace details. So, in the current version of the SolarWinds, SARS observability, it's possible to drill down particular LLM operations, and it's also possible to see them in the, in the context of other activities which are done, by the services. So if your, application is using some tools or some skills, which are under the hood, utilizing the, other standard services and other APIs, it's possible to track them from the very top to the bottom. So if I select, some, trace, it's it's the standard, let's say, trace, details are displayed. But here, the information about consumed number of tokens is displayed, about used tools, and also about model which was utilized by the, by the LMM operations. If we go to the particular, spam details, we can also, see all the LLM related attributes which are passed by the instrumented application, including the including the prompts and the conversation details. So currently, we have two levels which you can use. One level is this high level overview of the LLM usage by the services, and second level is possibility to debug your service activities, using the trace details. In the future, in the next quarter, we are planning to heavily, expand and evolve this functionality to make it, to be to be able to handle more complex, floats flows to be able to recognize, the sessions and, yeah, as I said, more complex LMM, activities. And this is everything regarding this subject. I will pass voice to the Adrian. Who is the next presenter? Thanks, Shrunk, and thanks everyone for joining us today. Shifting from Gen AI and LM observability, the monitoring infrastructure side. Tony already, briefed it, briefly teased it. I'm super excited to give you a quick look at the way we're proposing to simplify deployment and lowering the cost of ownership, for monitoring, your infrastructure with the brand new, light network collector. What we're proposing here is a lighter open telemetry based path to core network monitoring and SolarWinds observability, which should remove heavy dependencies such as the need for SQL server, IS, provide a smaller footprint, and overall lower the cost of ownership. It also supports both Windows and Linux, while the current network collector is Windows based. The new light collector is designed for faster deployment for your infrastructure dependencies. And, ongoingly, we're going to, be releasing this in a preview mode at the very beginning with limited functionality. And over time, based on, feedback, we'll react accordingly and increase the functionality, as such. The light network collector, focuses on discovery and monitoring, devices, metrics, interfaces, volumes. Right? So with the ACMP and SNMP in the very beginning. And features such as, topology, net flows, syslogs, and others, will come a little bit later. So, overall, this is not, new versus old. It's just a choice of how you want, to monitor your devices. Right? As we're going to expand ongoingly Adrian, you may have to share your screen. Yes. I will. I think we're a little bit past with the slides, but, I'll share my screen in a second, and I'll jump in the in the demo. Yeah. Nice place. Thanks. Alright. So, what we're proposing here is, at the very beginning, a preview that will help you, add network devices or simply just discover a range of network devices or on prem hosts as you're, already familiar with. Right? Like, and now with the new light collector, which, again, is in a preview mode, you'll have a simple choice to go and add it as your new flow. The deployment, as I mentioned, is much more lightweight to the current collector. It uses less resources, and the flow is fairly simple. Right? Like, it uses the same ingestion token that you're used to. You're able to deploy it, on Linux or Windows, and the installation is script based. Everything you need to do is copy the script to your, target machine. And in about two minutes, a new collector will be deployed. Now once the collector is deployed, we're tying up the experience into everything that you're already, familiar with in case you're using our SaaS platform already. You'll find under data collection all the agent based and agentless monitoring, capabilities that you have deployed already. So the new light collector will appear as a new tab. I have a few already deployed in here. You'll be able to see your workloads monitored by each. In this case, I have one that monitors already around 15, devices. If you perform a discovery, again, everything will be tied up in the same experience that you may be already used to. And you will find the discovery results under, the same tab under settings and network discovery, you would be able, again, at a glance to see, the resources associated to those machines. Right? Select and start monitoring, the respective devices as a network device or as a host depending on their nature. In terms of the details that we provide, again, ICMP and SNMP will be the first polling methods that we're introducing. And later on, based on, feedback and, adoption, we'll be moving to expanding the breadth and depth of the coverage that we provide to more complicated solutions, potentially API based, polling and others. What you see in here and in case you're already, familiar with our SaaS platform, should be already familiar. We provide the overview, the health details. Right? Everything that, we can monitor through ICMP, s n m SNMP, such as interfaces, volumes, and sensors. Again, ongoingly, we're committed to expand this. We're encouraging you to try it out once we're be releasing it in the upcoming, few weeks. And, let us know what you think. Now I'll hand it over to Sydney. Thank. you very much. Just before we wrap things up and dive into our q and a, we do have a few updates just on community as well as, events and, and an incentivized opportunity for you guys. So looking ahead, just as a reminder, one of the best ways to also connect with, both fellow SolarWinds users as well as our product team is through our THWACK community. Under the products tab, you can navigate to our SolarWinds observability SaaS hub. And through that tab, you are able to post different ideas, submit feature requests, and up, upvote any features that, you know, you really also are, you know, championing championing, as well as get updates on different events that we're hosting as well as, product and feature updates. The next thing that we are also doing, just as an incentive for our webinar attendees, is an opportunity, to participate in a g two review program that we are doing. This on g two is a great way to showcase your IT leadership and help peers, you know, across the industry, make more informed decisions about the tools that they are utilizing. You can share just, you know, your honest feedback on the platform as well as just how, you know, SolarWinds is working with your different workflows. And within this, like, these reviews can be completely flexible to, you know, whichever you feel comfortable with. And so they should only take minutes, and you can post both publicly as well as completely anonymously. And, just to help with that as an incentive, I will be putting up a poll soon. So, like, if you raise your hand, you will... You can claim 500 THWACK points, today just for, you know, saying yes to the poll. And then I will also be sharing a link to the campaign, within the chat. And the first 25 users who do leave a review, will receive a $25 gift card, once your review is published. And then following that as well as a bonus, you will also have the opportunity to win some SolarWinds merch as well as an additional 2,000 FLAC points. And so, again, these are quick and easy. The next step will be in our next poll just to sit... Select yes. And so I will open that poll. And anyone who is interested in participating, feel free to sec... Select yes, and then you will gain your first 500 THWACK points. And in addition to that, for those who are interested in leaving the review, if you leave a review, using the link that I just posted in THWACK, you will receive, the first 25 will receive a $25 gift card. So I'll give everyone just a few moments to complete the poll. Alrighty. And then just our last update before we get into our q and a section is, I'm sure an event that you may have seen promoted, but Solar Wednesday is coming up in a few weeks on October fourteenth and fifteenth. And the theme for this is introducing goal oriented AI. During this event, we will be diving into and explaining, you know, what exactly we mean by goal oriented AI, how it works, and what that means for your IT teams. We will also be showcasing some live demos, a look into our latest innovations, and a preview of our product road map. But the highlight, and you will definitely wanna join, is that we will be debuting a new AI powered product that will be joining the SolarWinds portfolio. So be sure to register for that, and that is coming up on October fourteenth and fifteenth. And with that, we can dive into our q and a. And we did have a few questions come up in the chat. We sure did. Yeah. Thanks again, everyone, for sticking with us. Really, some massively encouraging and truly valuable features there. So thanks to everyone who's presented. I think we just have one unanswered question. Looking through the the q and a there, I think we've answered most of those. But there is one remaining question on our back within LLM. So that's currently not there, Mark. The plan is to introduce roles for APM, in q one. That would, of course, then extend into the ABAC work that we will use to to support anonymizing data or extracting PII or other types of detailed information within those traces. That's very important for us to to hear that feedback, of course, as we we build towards expanding the RBAC framework, as we continue to focus on our number one priority for q four, which is that, access based, or attribute based access control across entities. If there is anything that comes to mind, following this webinar, please don't don't hesitate to reach out to any of us directly through the typical channels. I think that's everything on the q and a section that I can see there, Sydney. Adrian answered the question on the entities for the light collector, as you're licensing RBAC. There was one question I wasn't entirely certain as to the context. Is this a standalone server, or does it integrate with our existing Orion server? I tried to answer that thinking of, someone who's seeing SaaS for the first time. This is a a completely separate platform delivered, via SaaS, can integrate with your existing self hosted platform through Platform Connect. But, again, if there's any more, particular detailed level of a response that, anyone might need or if anything comes to mind following, the session, please let us know. What are the plans to make these improvements available for self hosted? There are plans for self hosted. We do have a separate series of webinars. We're very fortunate in the SaaS product team that we're able to iterate and deliver quite quickly. That is in contrast to the kind of fixed release cadence and upgrade cycle that accompanies a a self hosted, product. But there are plans to to keep those use cases and capabilities pretty much in in in parallel or, not deviate too much when it comes to solving the same problem. So things like open telemetry and cloud cost and AI capabilities, they should all follow, pretty much the same pattern across the portfolio. And there is one final ask, there from Cheryl. If you could bring back the QR code for a small bit. For Solar Wednesday. Never mind. This is a yeah. This is gonna be a very exciting, event for sure. Probably one of the the biggest announcements that we've made, over the last twelve to twenty four months. Really keen to see how customers are going to to adopt it and, and drive that value. It's, you know, a tremendous opportunity for us to bring the entire portfolio together using AI. I can't scan the code from here. The the link should work, I guess, that, promote the sharing in the chat there. Yes. Yep. Great. Thanks, everyone. So that covers the the q and a, and that's all from myself. Perfect. Thank you, everyone. Thank you all. Bye bye. Those great job.