How much is this slice of traffic really costing us, like in dollars, like right now?
For decades, that answer lived in pretty much spreadsheets, but today, it's a button.
So in this episode of Telemetry Now, I'm joined by Lauren Basile from Kentik to talk about how we can get instant traffic aware cost estimates for any slice of traffic, for any customer, for any ASN, and really whatever it's important to you. I'm Philip Gervasi, and this is Telemetry Now.
So, Lauren, thanks so much for joining today. It really is great to have you on. And this is the first time you've been on the podcast. So this is a special treat for me, especially and for our audience, I assume. But before we get started, I'd like for you to introduce yourself to the audience. Give us a quick idea of, what you do for Kentik, how you got to be be where you are today professionally.
And something that I talked about recently with Cliff also from Kentik was, what in the world is a is a product marketing manager anyway?
Well, thanks, Phil. I'm I'm really happy to be here and would love to dive into to all of that. So, as you mentioned, I'm I'm on the product marketing team here at Kentik. I've been at Kentik for about two and a half years now, and I really focus on the features, functionality, and capabilities within our platform that resonate with our service provider customers, so my mission is to really understand our service provider customers, their needs, their use cases, what challenges they're facing, what they're looking to achieve in our platform, right, and helping bring that to market. So I've, I've been in the digital infrastructure and connectivity space for quite some time now. I spent the first ten years of my career at various service provider companies, so mostly at Internet service providers, so ISPs and MSPs, managed service providers.
So I've worked all the way from really, really small, small MSPs selling, basic connectivity services to to niche verticals like health care. And then I moved on to Education Networks of America, which was an MSP that focused on, you know, selling to k twelve and higher education.
They were acquired by Zayo and so they're now the, like, education managed services arm of Zayo, and I was also at Zayo for some time, as part of that that acquisition, so I've spent a good a good, portion of my career, you know, understanding the, like, unique technology needs of different verticals and industries all the way, like I said, from education, health care to small to medium businesses, all the way up to large enterprises and understanding what solutions they they need to be able to serve their customers and their community. So that was everything from connectivity, network services, to security, and cloud, and voice, and UCaaS.
So very broad spectrum of, you know, IT, technologies. I've always been really fascinated with, technology and IT, and I love being on the product marketing side of that industry. So, as you mentioned, product marketing is actually a really, tough it can be a tough function to to explain because it's somewhat of a newer function within marketing within go to market. So traditionally, it's kind of explained where we are sort of liaisons of sorts that sit between all the different go to market teams.
So sales, marketing, product, engineering, customer success, all of these really important functions, and we kind of helped connect the dots.
But one of the ways that I like to explain it and indulge me with an analogy here is if you, have seen the the two thousand two movie drumline, I come from a marching band background. And in that in that movie, the the college marching band director has a phrase, like, an ethos that defines how he he leads that band, and it's one band, one sound. So really, each section of the band, right, has their own unique expertise. They bring a particular sound to the marching band, and each section is very important for the overall product and and performance and musicality, right, that the marching band provides.
But at the end of the day, it's about how these sections come together and how they all sound together in a cohesive cohesive style.
So I think of product marketing as kind of serving that role like a band director or a drum major or a conductor to a symphony.
We are the product marketing team works to make sure that all of the teams are coming together and how we talk about, our solutions, how we bring them to the market. It sounds like a cohesive message and voice and that we're making sure that we're we're centering the voice of our customers and the voice of the market in everything that we do.
That's a great analogy. Of course, now you're making me wonder what instrument I play or I represent here at Kentik, and, I don't even know. I don't even wanna go there. But that's an interesting background as well, and thank you for that.
I never really thought about product marketing in that way, and that really helps to kinda crystallize what that means. Like, you know, when I was talking to Cliff a Cliff, a few episodes ago, it was about product management, and we both joked about it. He's like, what is it? I asked him, what does it mean?
And he goes, I don't know. What do you think it means? He had an answer, but it was interesting to sort of, flesh that out because it is a little bit more nuanced than what a typical, you know, job description might outline. Right?
So Exactly.
So alright.
Money is important. Money is important to, organizations, especially if you're a for profit organization with a network, with data centers, with, you know, you're you're relying on the Internet and service providers, especially service providers themselves. I'm not aware of many, you know, not for profit service providers out there. So so if a CFO is coming to you or some sort of business leader and saying, hey. You know, what's the real cost of delivering this particular traffic to this particular region or to this particular customer.
Why has that been so difficult to answer historically?
Well, that's a great question. And the truth is it it seems kind of nuts, kind of crazy, right, that, these these network operators and service providers who, like you said, make their business, make their living off of delivering traffic, getting to that answer has been, very, very difficult for for decades.
And there's there's multiple reasons why it's so difficult, and we I'm sure we'll walk through them. There's complex billing structures and cost modeling. The dynamic nature of traffic itself makes that calculation incredibly difficult.
There's not really a clear owner internally on who really owns that because it spans both engineering and finance and sales. And then it's a lot of data that has to different data sources that have to be correlated together, And it it really requires a very purpose built automated solution to be able to to surface to surface those insights.
A purpose built solution. So so are you suggesting that there really aren't many, if any, purpose built solutions to solve that? Because you kinda, like, outlined that there is a solution. If you're able to ingest all of the data, analyze it, in in such a way where you can get those insights, well, there's your there's your answer. Right?
Yeah. I mean, so the data exists. Right? The the the problem is not the lack of data or network and infrastructure teams are having to manage mountains of data. It's making sense of that data and bringing traditionally disparate data sources together, and that live in different areas of the company, bringing them together into one one cohesive solution that's gonna give you the insights that you need. And that is really, really difficult and has been, that no one solve solve that issue yet, until until recently with, with Kentik and our and our new traffic cost solution.
Yeah. Yeah. So, I mean, you're talking about fragmented data. So the data that we care about, with regard to specific customers or right from the network itself, so network metrics.
Right? All that stuff lives in different places. It's also different forms and formats. That's that's an issue in just data analysis in general.
Right? So how how do you, look at both, you know, SNMP traps and streaming telemetry and flow data and, you know, metadata that you stick in there from your customers and and things like that, all in the same, you know, in the same portal, in the same screen.
And and it does require some some effort. And I think that's that's probably, an issue for a lot of companies out there that are dealing with disaggregated networks, distributed networks, service providers that are really making so so little money, per, you know, packet that's sent over their network that they really need to be very, very in tune with what's going on at that kind of granular level.
So, you know, what what is the, the result? It's, you know, this idea that we have all of this data, but we don't know exactly what's going on. Is that about right?
Yeah. So if we if we kind of unpack this a little bit, right, the network operators, service providers, anyone who's who's running or operating a network or the network is central to their business, they're they're gonna have costs associated with delivering and receiving traffic. So those are the connectivity costs. Right?
These are the costs at the network edge. They're the cost of exchanging that traffic from one network to another, and they these exchanges really form the connective tissues of the Internet. It's how, right, it's how traffic is able to, transport from all of the content providers, from the cloud providers, and get into our, you know, our hands as consumers and our our eyeballs and and how we how we consume traffic over the Internet. But each of those interconnection points, those exchanges has, there's different connectivity types.
Right? So you can pay for, you could have multiple IP transit providers that you pay, upstream to help you deliver your traffic across the Internet. You can be a member at multiple Internet exchanges, right, and be able to to, join that exchange and peer with their membership within that peering fabric.
There are, you know, paid and free peering. Right? So those all have you in in private network interconnects and backbone and metro transport. I mean, there's so many different types of connectivity that each of these exchanges can have, and there's multiple providers within each of those types of connectivity.
And so each of them are, a complex cost modeling. I mean, the way the way you're billed and the way that you pay for these services from your service providers, there's so many different types of of cost modeling and computation methods. There's flat fees, there's tiered rates, there's ninety fifth percentile, there's bursts in overages and commitment rates, so it's the the complexity at scale quickly becomes, you know, very very overwhelming and then if you add in global variability, if you have a global network and you have different, currencies that you're working with, you have to convert currencies and, the way that traffic is billed is dependent on the billing direction.
Right? So circuits are bidirectional and depending on the volume of traffic on which direction, some networks are gonna be charged for most of their their traffic's gonna be ingress. Right? Other networks, it's gonna be egress.
And so you have to take that factor into account when you're looking at at cost structure. So all of this, complicates is is very, very difficult to do when these these contracts typically live within legal and finance departments and being able to map each of those cost structures to all of your network topology, to all of your interfaces is really step one, right, is kind of the base layer of understanding who who am I paying and how much am I paying for connectivity, each month? What does that look like, the spread of that look like across peering and transit?
And that's that's really the foundational step one layer, but then getting to, well, what is actually driving those connectivity costs is the next level that has been super difficult for teams to be able to to understand. And, I I like analogies, so, I'm gonna present another one here where I if we think about in our own our own daily lives, you know, if you get a credit card statement, right, you you spent five thousand dollars last month. Well, your connectivity costs are gonna tell you, okay. I spent eight hundred dollars at, you know, Walmart.
I spent three hundred dollars at DoorDash. You know, no judgment. I spent five hundred dollars at Trader Joe's. So you get the very high level, like, this is how much I spent with who.
But what we really need or is this kind of this next layer down to understand what is driving my spending in the first place. What are the events? What are the categories? What are the things going on in my life that I need to be spending that money on?
So we like to categorize and attribute some of those costs to other things. So for one example, right, could be just like groceries.
So of the eight hundred dollars you spent at Walmart, maybe only three hundred of that was groceries. Maybe four hundred of that was, you know, towards, like, outdoor equipment and and summer activities. Maybe a hundred was towards your child's, like, birthday party or a vacation or something. Right? We wanna be able to attribute portions of these costs that we're making every month to different categories and themes. And so that's really what the next layer of this traffic based, this traffic aware cost intelligence is needed is to look at our to look at connectivity costs and be able to say, I can see how much of my connectivity cost is being driven by this particular ASN, this particular market, this particular customer, and see how it's driving those costs. So every single path along the way from every interface that's that's producing right the amount, the the effective cost per megabit per second for that.
You're giving me heartburn, Lauren, listening to all this because this is so nuanced. I didn't even realize that having a more enterprise networking experience, you know, I I'm aware of the service provider side. I get it. And I'm always thinking, well, packets are packets, you know, whatever.
That's that's not the case when the network is the product, right, that you're selling. And you you do care about every single packet and where it goes and why. And, you know, and I and I always default to, like, the engineering part, the route the routing and the, you know, how do I make this more efficient from that perspective. But my goodness, you just gave me all this qualitative data.
You talked about contracts and, different currencies and, you know, there's probably like, should we renew this contract or not? And is this transit over here less expensive or more expensive?
And does, you know, taking the less expensive route, is it a little bit more latency? But who cares? Because we save a bunch of money. I mean, there's so much nuance.
It's crazy. I mean, what what is the ultimate result, though, for a service provider? Is it really just saving money? I mean, that's is that the the the goal?
So there's there's a couple of key outcomes and and values that they derive from this type of this insight and and cost visibility and analytics. Right? So, of course, saving money is one of those components. We we talk a lot about how network operators, right, they're really optimizing for three core foundational needs, cost, performance, and security or reliability.
Right? So making sure that they're they're cost optimized and they're efficiently delivering traffic, making sure that their performance is up to par and that they're providing a great customer experience, and then that their network is protected and secure and and reliable. So this definitely falls very much into the cost versus performance trade offs that you were talking about. If I it's it's easy or I should say rather, it's it's more common to be able to optimize for two of the three.
It's really hard to optimize for all three at once. Right? So there's a lot of times these trade offs that network and infrastructure teams have to make. Is it does it does it make sense for us to invest a little bit more in connectivity over here for a greater performance because we're getting a lot of revenue from that traffic delivery?
Or if we're not getting a lot of revenue, maybe it's worth going with a cheaper transit or connectivity and sacrifice a little bit on performance, but it makes sense for our business. You really can't make those trade offs and have data backed decisions with those trade offs if you don't have the economic data behind traffic delivery. So that's that's one component. And then you you touched on margins.
So the network has always been compared, at least from the Internet scale, right, that there were the plumbing of the Internet. Right? And, and prices have commoditized in the industry over time. Competitiveness has gone up, which is also driven pricing down.
And so margins on a lot of these, these services have gotten thinner and thinner over time. And so getting visibility into how much is a customer's traffic costing you to deliver is really, really key to understanding you the health of your margins. If you don't know how much your one of your downstream customers is costing you, how much their traffic, is it expensive traffic? Is it cheap traffic?
Right? I can't compare what I'm pricing per megabit per second for that service to see if I'm in if I'm in the red or if I'm in the black. Right? So getting getting that data is is really powerful when they're coming up on customer renewals to understand, okay.
Maybe we need to charge this customer a little bit more, a little bit above the market rate, but we have the data to say, you know, your your traffic is costing us this amount per month.
And then the last thing I'll I'll mention is I think that, you know, in the age of AI, we're under this, like, ruthless pursuit of efficiency, right, at all costs. Like, so anything in this day and age that still relies on manually gathering data, on manual correlation, anything that's not automated or using AI to reduce the time to execute on that task or exercise is just not it's not okay anymore. Right? Engineering and infrastructure teams are already lean.
They're getting leaner. They're having, they're expected to use AI and automation in their work. And so doing all of this manual, cost tracking is is not really realistic and because of that, it gets lost, right? They may prioritize doing a couple of calculating a couple of these costs for various slices, but, oftentimes, it's it's lost.
It's not real time. Right? So you're getting charged every month for connectivity. So this isn't just a one and done exercise to be able to track trends over time.
You have to compute and calculate these costs every single month to see if you're making progress towards your financial goals. And so being able to do that is just completely is completely unrealistic without some automation.
Oh, yeah. Absolutely. Absolutely. So you've been talking about data quite a bit, and it is interesting to me, and we've already known this that, you know, the the data that we get, the hard metrics that we get from the from the network, from service provider networks, even on a small scale, they're directly correlated to real dollars.
So I get that now. But what data are we talking about? Now you mentioned a a variety of type of types of data, which we understand are in different formats because a contract is different than an SNMP trap. Right?
They're very, very different things. So let's talk about that. How does this work? What kind of data do we need to gather and ingest into a system?
And, and when I say a system, we're talking about the traffic costs component of, what we do with at Kentik.
So what kind of data, what would those sources be, and and how does that work?
Sure. So, yeah, we so we let's unpack those different those different data sources. So first and foremost, you're gonna need access to your contracts. Right? Everyone that you're paying for for connectivity and interconnectivity across your edge, you are going to need to get that from legal teams or wherever it lives within your your company and your organization.
You're gonna need to know, what that cost modeling is. And earlier in the episode, I mentioned there's so many different types of computation methods and and modeling, but you're gonna need to have that first. And then you're gonna have to map that those cost structures to your your network topology and to your interfaces so that you know which of your interfaces are, you know, internal versus external, and you can apply that cost structure to each interface. Right?
Because traffic is dynamic. It's going across dozens, if not hundreds, of interfaces, and so you're gonna need the cost structure for every single interface, so that you can pull that for whichever whatever traffic slice that you want to price. So those are the kind of the first two two components, and then you're gonna need to pull in, s and m p utilization. Right?
So the way that you're billed is off of utilization of that of that interface and the the volumes of traffic that are going across the interfaces.
So pulling typically, that's, you know, five minute s and p pulling and, that factors into the the cost modeling.
And then the the next layer or the final layer is flow data. Right? So the s n and p data will give you the volume of traffic, but it won't tell you what type of traffic it was. It won't tell you where it was headed or any of these other dimensions, right, that that flow data provides. So then you need to layer on the flow data on top of it so that you can actually pull the different slices or the different dimensions within that traffic to understand if I wanna pull by an, source or destination ASN, if I wanna pull by a particular customer, you're gonna need to have that flow data correlated there too. So it's really bringing together four four different sources.
Yeah.
So Four very different sources. I mean, SNMP and flow are different for sure, but they're still, you know, they're still metrics. They're still, it's still structured data that we derive from network devices and and network adjacent devices.
But not so when you're talking to the legal team and getting contracts and that sort of information. And, you know, so these four areas, are are very divergent.
And, yeah, I I can imagine that if you're doing that manually and you're doing the the old stare and compare of contracts and interface information and and, you know, some flow record, trying to do that manually, even if it it's a team of smart engineers, it's gotta be error prone, an incredible, inefficient time, you know, use of time, that sort of thing.
When you say slice though, network slice, what does that mean exactly?
So I think about it as we with the flow data, we can precisely map, right, a slice of traffic across your network. So we can see exactly if we let's take a customer, for example. Right? If you wanna see one particular customer's traffic that's going across your network, you need to be able to see where it's entering and all of the exit ports or vice versa where it's and it's it's, exiting and all the entry ports and be able to isolate that slice of traffic across all of those different entry and exits.
And so that is what we mean when we say slice is being able to to provide a map of that one particular dimension of your traffic and find everywhere across your infrastructure, it is traversing an interconnectivity exchange point. Right?
Yeah. Yeah. So I get it. So what you're doing is it's not just saying flow and SNMP better together.
I mean, that is true. They are better together, and they and that that is a pillar of what we're talking about here. I get it. But it is a lot more than that.
I mean, you really are mapping whatever is important to a particular provider, whether it's, an ASN like you said, or maybe it's a CDN so they're looking at some over the top service. What whatever it happens to be. And then, like you said, you can map all of that information specifically to the specific cost models applied to the interfaces that are relevant to that that that network slice.
Now, lo and behold, at the conclusion of that exercise, you have a very clear understanding of what it costs for that specific activity on your network. So, you know, on all your routers and switches and fiber links and SFPs and all that stuff that's cool to engineering, but, all of which has a very, very clear relationship to dollars and cents. It sounds like the break that's really the breakthrough here is the idea that we can put all of this together and programmatically, like you said, where we're looking at, yeah, we're looking at all those routers and switches and and SFPs and fiber links and all those kind of things. You mentioned some Internet exchanges. All those hard metrics alongside with, like, what does it cost per ingress, egress on that specific port, mapping all of that together.
So that way, this this network slice, whatever it happens to be, whatever whatever the provider cares about, whether it's, you know, a specific region or a specific customer, a specific ASN, a specific, you know, if it's a CDN, maybe an over the top over the top, application. Whatever whatever it happens to be, whatever is important, we can map, literally bits going through wires to to to a cost and and then really understand it that way. So, you know, that that I think is probably next to impossible to do quickly and efficiently using the old stare and compare method like I alluded to earlier. So so, you know, that that's all great. How how do we solve that? How does, and how does Kentik specifically solve that?
Well, Kentik specifically solves that by really working through. We we've developed over the last couple of years that exact, step by step process that I was talking through earlier. So a couple of years ago, we launched, connectivity cert connectivity costs, rather, and that was our first, you know, cost intelligence workflow where we merged, right, the contractual cost data with the network mapping and the s n and p utilization, giving Kentik users the ability to track how much they're spending with each provider, how much of their connectivity costs are transit versus peering versus IX, that distinction, and they can they can at least validate their invoices.
They could spot maybe some issues with invoices and address those with their with their connectivity providers, and then they could track some overall costs over time. You know? Am are we spending more with one provider versus another? Does it make sense to renegotiate our commitments with them?
You know, so kind of giving that first layer. And what we've been building since then and sort of really the the the end game, I should say, or the the goal of setting up that foundation was to get to this point with with traffic cost today to be able to tie traffic behavior, traffic patterns, traffic dimensions to the dollars of of delivering that traffic. So and and that's what we built. Right?
We layered on the, Kentik's contextual contextually enriched flow data, which enables us to be able to precisely map everything by OTT, by CDN, by customer, by ASN. Right? That all relies on the NetFlow data and the enrichment that Kentik provides on top of it to be able to map in those particular dimensions that network operators and service providers really care about. Right?
And that's what they're they're really trying to get from from this data is the cost to serve. How much is it costing me to serve a particular region? If I'm a, you know, if I'm a a content provider, I'm an over the top provider like Hulu or, you know, Amazon Prime or Netflix, I wanna I wanna understand how much is it costing me to reach a particular region, a geographic region, or particular broadband, ISPs, right, that's that helps serve that content. And I need to be able to compare how much it's costing me to serve that traffic versus the revenue that I'm getting from from that region.
That helps me decide, okay, do we need to optimize the way we're delivering traffic? Do we need to change pricing and vice versa? Right? So if I'm of the broadband provider in this instance, I wanna know how much it's costing me to serve all of those application, all of those streaming platforms' traffic.
And so then this gives this gives, you know, engineering edge strategy and interconnection and peering folks the the insights they need to go and see, okay, these are the highest cost paths that these these slices are are taking.
How can we optimize this? Can we set up new peering arrangements? Do we need to change our traffic engineering a little bit in routing to to better to better have that delivery?
So it's really giving them the insights that they need to not only optimize spending and reduce spending, but to to make that spending versus, performance trade offs and then to increase increase revenue, right? If they know how much it's costing them to serve, they can make strategic decisions to help grow the business. And then, of course, the operational efficiency, as we've noted. I've talked to many customers during this, during this process of developing traffic costs, and it's real we're talking weeks, you know, hours upon hours or weeks to be able to derive, calculate just a couple of slices.
So when we're really automating that in a couple of clicks, within Kent.
Right. Yeah. Again, making what's otherwise very, very difficult to do. You know, the data's there, but doing it in a programmatic way.
But but also adding in those other things, this kind of, like, data analysis as a service because you you did talk about correlation. You did talk about, enrichment. So adding this additional data to what is ultimately a database under the hood, you know, that computers, understand and and do joins and and, you know, data cleaning, all that kind of stuff. All the stuff that you as a network team or as a business team that relies on the network at a provider would need another team, otherwise known as data engineers and data analysts and all these types of folks to to manage and figure all this out and give us that that that business insight.
Now that is actually something I wanted to talk about because you have talked about several different personas. You've talked about network engineers, or I seem I assume you meant that when you talked about traffic engineering. Right? That's who's usually doing that. So they're looking for those high cost routes, and they're getting the data, from the network. They're comparing that with, you know, contracts and and all these other things.
But you also talked about business decisions. So it sounds like, this entire, this entire functionality really lends itself to multiple teams. This is not a networking tool or purely a business insights tool. Correct?
Yeah. That that's correct. This traffic aware cost intelligence and cost visibility, cost analytics, whatever you wanna call it, really lives at the intersection between network operations and business operations.
And so that has been another challenge, right, is democratizing these cost insights to more teams within the business that can derive value. So while the engineering teams are going to be really the practitioners living, you know, living and calculating and and doing the the data, analysis, being able to share that with the commercial teams, with with sales and and product, who are really the ones spearheading, like pricing and negotiations with customers and customer renewals, they're gonna really they're gonna need this information. And so coming up with a way to democratize that to other areas of the organization and then being able to easily share this data where anyone in the organization can either log into Kentik and get the personalized view that they need of the cost and slices that they that they care about or to programmatically send it their way to create reports, right, that they're gonna consume and they're gonna be able to use and make and make decisions based off of.
So a network engineer can log in, look at the same portal, kind of adjust the dashboards, within traffic cost to understand, alright. Are there any QoS policies I need to adjust on these particular interfaces? Whereas somebody from the business team, same same traffic cost portal, but the you know, with their own view, their own widgets and stuff, can understand quickly, how are things trending in this particular region and why, and how can we make business decisions and adjust accordingly. Right? So, really, this, this really does kind of, link the business and the technical worlds in a way that, I mean, I I have never really seen before. That's usually something where, you know, you throw something over the cubicle wall and you have that kinda, like, Slack interchange and you have those those discussions. And and back in the day, I almost said Webex.
That's crazy. But you have your Zoom meetings to discuss and kinda brainstorm. So let's say that you're you're new to this, not you, Lauren, but a a provider that's listening. What's a good first network slice to sort of snapshot to get started with understanding traffic cost?
Yeah. So it's actually going to depend heavily on where you sit in the sort of Internet traffic delivery ecosystem, as a network operator. Right? So if you're a, eyeball network, if you're an access provider, like an ISP, you're really gonna care about the slices of traffic, how much it's costing you to serve all of the the top content platforms, gaming platforms, video platforms that make up a majority of the traffic that you're that you're, you know, ingressing.
On the flip side, if you are one of those platforms, you're gonna care about how much it's costing you to serve that traffic to those those markets and those destination eyeball networks. If you're a wholesale provider that's in the middle, right, you're gonna care about your customer margins the most and being able to pull how much a particular customer is costing me and and to do that margin analysis exercise. So it really it really depends, and I think that's the power of having so many different dimensions and the traffic to be able to slice and dice by is that each side, each area of the Internet ecosystem can derive the insights they need, to make better strategic and data backed decisions.
Yeah. Yeah. And the data is there, so you can do it regardless of your specific role in this entire application delivery system.
So, Lauren, I think this is a good spot to wrap up. If folks are interested in learning more, and I know they are, where can they find more information about Kentik Traffic Costs?
Yeah. So you can head on over to our website, Kentik dot com, and look at our our recent blog post on traffic costs where we break down really how the workflow operates, all of the information that you can see within the platform for traffic costs. And then you can sign up for a demo, and our team will be in contact, you know, really shortly and kind of give you that personalized walk through and then show you the the vow the the value and the and the power of being able to to derive these these cost analytics and and insights.
Great. Thank you so much, Lauren. It's been a real pleasure to have you on today, and certainly, I hope that it's not the last time as well. And to our audience, if you have a comment for Lauren or perhaps a question about today's episode, I'd love to hear from you. You can reach out to us at telemetrynow@kentik.com. So for now, thanks so much for listening. Bye bye.