 from our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBE Conversation. Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in our Palo Alto offices for a CUBE Conversation today. We're going to talk about an interesting topic. You know, as all these applications get more complex and they're all internet based, I'm sure you know that feeling when you're at home and you lose your internet power. You pretty much can't do much of anything. So what can we do about that? Who are some of the companies that are working on this problem where we're really excited to have an innovator in the space from ThousandEyes? She's Archna K7, Director of Product Marketing, for ThousandEyes, welcome. Thank you, Jeff. It's good to be here. Absolutely. So this is crazy. Give us kind of the rundown on ThousandEyes and what you do and then we'll jump into it. Sure. So ThousandEyes is a company that provides and enables enterprises, gives invisibility into how the internet is impacting end user experience, right? And when you think of it of what users are or what this user experience is, it could be twofold. One is if you're an enterprise providing a digital service and they're your customers, right? So that customer experience, we provide visibility into that. And then also if you're an enterprise, you know, moving towards using cloud applications or SaaS applications, you know, we understand employees using those applications, we provide visibility into that space as well. So really the thought and the idea behind ThousandEyes and the reason we are here is as enterprises are moving to the cloud and relying on this internet-based delivery infrastructure, they're starting to lose visibility into their critical customer-facing and employee-facing applications, right? And what ThousandEyes does is it gives them back that control by giving them that visibility into that environment. Okay, so just to be clear, because there's a ton of kind of monitoring applications, we're just assuming logic, we do Splunk. So there's a lot of things around operations where they're monitoring these apps and they're super complex apps. But your guys' main focus, if I understand, is the network, right? Or the network piece and the transportation of that app across the wire. Right, so let me unpack that and explain that with an example, right? So let's think you're an enterprise that's moving towards Office 365 and you have a global workforce, right? And your users are connecting report and your VP of sales happens to connect from a Starbucks or it fills because we're in Palo Alto, right? So can download emails, can get to emails, what's the first step this person or this employee is gonna take is call corporate IT and say, hey, I can get to my emails. Now it's up to the corporate IT team to go and troubleshoot that scenario, right? Because if you can get to your emails or you can get to these collaboration apps today, it's productivity down the hill, right? So the IT team now starts troubleshooting it and where do they start? Is it the wifi at the fields that's a problem? Is it Microsoft that's a problem? Because of which I can get to my email or is it that access in between? Which is the internet, right? How do you get from a fills all the way to Office 365 is through that internet transport, right? So what we, where we come in is irrespective of, you know, the application or even the network, right? We're very agnostic to it and we combine application performance all the way to the network performance. We take it one step further and we see how the internet is impacting this service as well, right? Because what we see is our customers be that in enterprises consuming SaaS or enterprises delivering these SaaS services, the production teams and the corporate IT teams, they feel the brunt of this every day. They have people calling and saying, hey, I can't get to this, I can't get to that application. They have their own customers complaining that something's wrong, right? And unfortunately in this world of the internet and the cloud, while it's enabled, you know, convenience and flexibility, they've created in that for control and visibility, right? So if you, again, go back to this Office 365 example that, you know, I was just talking about the enterprise does not own the WiFi in false. It does not own the internet. No one entity owns the internet. Doesn't own Office 365. So monitoring tools that have existed and that have been in place to understand issues within the four walls of an enterprise flat line when it comes to internet-based delivery and connectivity, right? Which is where we come in. So what about like VPNs? Because this isn't kind of the purpose of a VPN on one hand is to be secure because Lord knows who's sniffing on the Phil's WiFi. But does that not put you into, you know, kind of a higher grade, you know, internet line back to the server to get to my email? Is anybody using VPN these days? I hear the ads all the time on the radio. I don't know, it's a good question. You guys are sitting on, are people not using VPN or does VPN solve the problem? Or is it something that's on the backside that regardless of whether you're using VPN or not, these are kind of backhaul issues that have to get flushed out. So VPN, if you think about it, it's kind of an encapsulation over the underlying network. You still have to move packets through this network, right? So you might be connecting through a VPN, but it's the underlying, if you're going through the internet, then that can result in performance degradation too. So irrespective of, you know, these techniques that enable or so-called enable performance and make performance better, you still need to know what the transports, how the transports we're having and how it's influencing performance just because you don't control it. Right, right. And as I understand the way you guys are doing this is you have a lot, a lot, a lot of monitoring points all over the place, heads, thousand eyes. Right. So I'll just ask a little bit about, you know, kind of how that works, what's the network, you know, how's that been growing over time? Right. Yeah, so we've been growing our infrastructure, monitoring infrastructure over the last few years. And the way thousand eyes gathers this data, which, you know, all the way from the application layer to the network. And I've been looking at internet performance, is our fleet of agents are distributed, are pre-deployed in about 185 cities around the world. We call them cloud agents. Now these agents are actively monitoring the services that might be of interest to an enterprise. You can also take a form of these agents and, you know, enterprises can deploy them within their own branch offices and their data centers. You can also use them in cloud providers. So we actually have agents pre-deployed in AWS, Azure, Google Cloud and Alibaba too, which we recently announced. And you can use these agents to monitor applications. You can use these agents to monitor your API endpoints, which is, you know, another growing area that we see. So yeah, so fleet of our agents distributed, you can use that combination of agents that we own and pre-deployed along with agents that enterprises would like to put in their own infrastructure. Right, so you've got the ones already out there, you've got the ones in the clouds and then I can put some additional ones into my remote offices and other places that are of interest to me. Okay, and so if there's an issue, because as you said, for tech support when the person can't get into email, there's a whole host of potential things it could be, right? Office 365 could be down, there's all kinds of things. So how does your application communicate to this poor person on the end of the service call that, hey, it's a network issue between these two points or it's a, you know, maybe it's a big exchange that's getting attacked like happened on the East Coast a couple of years ago. How do they work that into their triage so they know, hey, we've been able to kind of identify that this is the issue, not one of the other 47 things that's impacting that application. Right, right. So we are a SaaS based product and the way we and our uniqueness and our secret sauce is how we look at all of these different layers that affect performance and we correlate them, visually correlate them in a time sequence and we present it to the corporate ID person or a production ID person who's like actually triaging this issue and we help them very quickly pinpoint. It's very visual there. You can see how application performance, you know, ebbs and flows. You can look at what is a network path look like, you know, if I'm seeing an outage of an internet service provider, we're going to call that out. And obviously all of this is, you know, tied in with an alerting system which the platform enables as well. I think one of the most interesting changes that's happening in the industry is in the past when you found an issue, you could fix an issue because the chances are you own that entire environment, right? It was a router that failed or a switch was dropping packets, you own that switch, you own that router, you could go and make changes to it. But in today's internet dependent and cloud heavy environment, it's more about having the right evidence so you can escalate it to the right person, right? So knowing which neck to choke is absolutely critical in this distributed environment that enterprises are losing control over slowly. So the people start to make active changes in the way they route their traffic based on, you know, what they find is their, you know, kind of consistent, either consistent good or consistent bad behavior in certain networks or certain public clouds that you can, you can get a better latency performance by switching that. Sure, we've seen cases where, you know, if one, if usually enterprises have like, let's take an example of an internet service provider having an outage, right? And usually enterprises, you know, for redundancy they have two upstream providers, for instance, and they're probably load balancing traffic equally across these providers. Once thousand eyes detects that one provider is completely down, could be a routing issue, could be a router failed within their environment, once we alert them, it's up to the enterprise to make that decision saying, hey, we want to bypass this route, right? And we've seen that happen in a lot of cases. They do bypass routes if it's possible. Also depends on the severity of the issue, how long the issue lasts and things like that, but that definitely happens. So you guys talk about a concept called internet aware synthetic, what does that mean? Right, synthetics, it's interesting as a term, what it really means is trying to mimic something that's natural, right? Just the term synthetics and then layman language, right? So synthetic monitoring is really just that, is while you're trying to understand application performance or how a website performs, synthetic monitoring replicates how a user would interact with that application, right? And you replicate those steps and you periodically repeat them over time. Let's take an example, you're shopping online, right? You're going to amazon.com, you're searching for whatever it is that you're searching for, you get a list of results, you are interested in one item, you look at a review, you seem relatively happy, you move it to your checkout, pay and move on, right? So those sequence of steps is what synthetic monitoring can actually craft. And we keep executing those steps periodically so you can understand if there's any degradation of performance, has it slipped from baseline? So IT operations team can use that to understand if there's any change that's happening or if there's a particular area in the world where users are starting to see degradation and so on, right? The nice thing about synthetics is it's proactive. There's a lot of monitoring techniques out there that looks at real user interaction with a website, right? And to use typically do that, you need to insert a piece of code within the application itself, the tracks that users activity. And that's great information. You want to see what your users are really doing and engaging with your website, right? That's very useful, but it fundamentally doesn't tell you if performance is completely degraded or the checkout button's not working for instance. And that's where synthetic comes in. So is that the primary way that you maintain kind of this testing of the health of the network or are you using more of a passive, waiting for something to be slow and then running something like the synthetics to try to figure out where it is? The recommendation is to keep synthetics running constantly, right? Because you don't want something to slow down and then react, that's a very reactive approach. And really in today's digital economy, you don't want an outage to last too long, right? Because customer loyalty is fleeting. You don't want even 30, 10 seconds of wait time, right? Like the way I see it is every time I try to find a cab through Uber, if Uber makes me wait 30 seconds, I'm moving on to lift. Like I don't have the patience to wait that long. So you don't want outages to prolong. So you definitely don't want to understand performance after it has degraded, right? So synthetics recommendation is to continuously monitor so you can find out what's happening and if there's any drift from required baselines. Okay, and then are you running that concurrently across a number of geographies for the same customer? Because if the same shopper is sitting in Seattle versus if that same shopper is sitting in Mexico City or they're sitting in London, are you running that kind of concurrently to make sure that you're checking all the different potential hiccups? So the, our agents, because they are so pervasive across the globe, you can pick an agent in one of those 185 cities and you can execute those same sequence of steps over time to actually run that, right? Now, synthetics as a technology is not new, right? It's, it really predates the cloud, the way, like the action of, you know, mimicking a user journey through a website that really predates the cloud, which is why it's fundamentally broken when it comes to these cloud and internet heavy environments, right? So what we introduce, Thousand Eyes Internet Aware Synthetics tries to take this age old technique and, you know, tie that together with how the network and how the underlying internet performs. So when you're looking at performance, you're not looking at it in a silo, right? Because that's the other thing we hear all the time from our customers, right? Like the application team has blinders on. They're wanting to see if anything's gone wrong with the application. The network team has its own blinders on wanting to see if anything's gone wrong with the network, right? And usually what's happening is if they figure out it's not an application issue, they punt it over to the network team. The network team says, ah, not my problem, you take care of it. So there's this constant finger pointing that happens in today's environment, right? And this pain has really, you know, gotten worse in the era of the cloud and internet-based deliveries. Because guess what? Like your application is first of all, you know, split into these microservices. The number of API calls that you're making has gone up, right? And all of these components don't sit in the same place, right? You're probably running into a hybrid infrastructure environment where some pieces of your code resides in your data center, the other might be in the cloud. Or you're making API calls, which is resulting in a multi-cloud scenario. And what is it that's connecting all of these, you know, different environments as the actual network and the internet, right? So understanding just, hey, my app is down, it's not good enough anymore. You need to know, my app is down, it's down because the internet is causing problems, for instance, right? So what Taazana is internet aware or network aware synthetics does is we look at performance right from the application stage, look at all those transactions, see if they are getting, you know, they run correctly or not. We tie them into how the underlying network is performing. And hey, if the internet is causing issues, we tie that into in a single correlated pin. So, you know, you're looking at one single platform and you're able to pinpoint quickly. So you've gathered the evidence to escalate it to the right person. And at the same time, you are bringing the application and the network teams together. So it's more collaboration. It's not finger pointing. And that's really what we want to enable and what most of our customers actually do with Taazana. Okay. So before I let you go, I want to dig into the Alibaba announcement a little bit more. You know, China is a special challenge on the internet space. And you know, we've done some work over there and you know, like none of the Google services work and we use a lot of Google services. So, you know, how did that come about? Is this a new and growing area for you? I would presume there's all kinds of demand from the customers to try to get a little bit deeper penetration into that marketplace. China definitely is an interesting space, right? I mean, because of the great firewall and all of the techniques, you know, China implements, performance is known to be relatively suboptimal in that region. And fortunately or unfortunately, it's the fastest growing market too. So enterprises want to invest in China, right? So we're seeing a trend where they are moving their services to Ali Cloud. What does that mean for enterprises, right? You need to monitor that environment too, which means you want to understand how performance is from Ali Cloud to Ali Cloud and so on. So what we did recently is we increased our vantage points within Ali Cloud. So now you can look at user experience for users connecting all from all around the world into Ali Cloud. You can look at, you know, API performance going from Ali Cloud to GCP or AWS, right? And I think the key point to remember is that not just in China, but across the world, not all cloud providers are created equal. We found some very interesting data that, you know, for traffic between Beijing and Singapore, Ali Cloud performed relatively better. No surprises there, but AWS was, you know, had relatively high performance. Same user from Beijing to AWS's data center in Singapore, they had a very circuitous route to get to Singapore. They were going from China to Tokyo to Singapore. And during peak times, 8 a.m. to 8 p.m. Beijing time, there was a lot of fluctuation just showing that there's some kind of congestion in the network, right? Ali Cloud, we didn't see that. So, you know, understanding cloud provider performance is absolutely critical. And what we do is our vantage points enable enterprises to do that. And one of the initiatives at Thousand Eyes that we have been doing for a couple of years now is do a comparison of all these providers, AWS, Azure, and Google Cloud, and Ali Cloud now. So last year we had our first report. It's called the Public Cloud Performance Benchmark Report that compared AWS, GCP, and Azure. This year we're expanding it to Ali Cloud as well. So that's launching in November. So it's going to be interesting to see. A lot of people don't want to see that one. Yeah, it's going to be interesting to see who performed better and where. It's always good information. I was going to ask if you could share, but I didn't want you to give it away any secrets. But I guess not, I just got to wait till the report comes out in a couple of months. Yep, mid of November, it's going to be there, yep. All right, so we'll look forward to that. And I'm sure it'll be more variable than most people expect. We'll see. All right. Well, thanks for having me, Jeff. Thank you very much. All right, she's Archnaum. Jeff, you're watching theCUBE. We're in our Palo Alto studios. Having a CUBE conversation, thanks for watching. We'll see you next time.