 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 studios today to have a CUBE Conversation with a really exciting company. They've actually been around for a while, but they've raised a ton of money and they're doing some really important work in the world in which we live today, which is a lot different than the world was when they started in 2010. So we're excited to welcome to the studio who's been here on before, Mohit Ladd. He is the CEO and co-founder of ThousandEyes. Mohit, great to see you. Great to see you as well, thrilled to be here. Yeah, welcome back, but for people that didn't see the last video or not that familiar with ThousandEyes, tell them a little bit kind of what is ThousandEyes all about. Absolutely, so in today's world, the cloud is your new data center, the internet is your new network and SaaS is your new application stack. And ThousandEyes is built to be the only thing that can really help you see across all three of these, like it's your own private environment. I love that kind of setup and framing because those are the big three things. And as you said, all those things have moved from inside your control to outside of your control. So in 2010, was that the vision? I mean, when you guys started the company, UCLA, I guess a while ago now, was that the trend? What did you see? What kind of started it? So it's really interesting, right? So our background as a founding company with two founders, we did our PhD at UCLA in computer science and focused on internet. And we were fascinated by the internet because it was just this complex system that nobody understood, but we knew even then that it would meaningfully change our lives, not just as consumers, but even as enterprise companies. So we had this belief that it's going to be the backbone of the modern enterprise and nobody quite understood how it worked because everyone was focused on your own data center, your own network. And so our entire vision at that point was we want people to feel the power of seeing the internet like your network. That's sort of where we started. And then as we started to expand on that vision, it was clear to us that the internet is what brings companies together, what brings the cloud closer to the enterprise, what brings the SaaS applications closer to the enterprise. So we expanded into cloud and SaaS as well. So when you had that vision, people had remote offices and they would set up, tunnels and peer to peer and all kinds of stuff. Why did you think that it was going to go to that next step in terms of the internet, just kind of the public internet being that core infrastructure? Yeah, so we were at the very early stages of this journey to cloud, right? And at the same time, you had companies like Salesforce, you had Office 365, they were starting to just make it so much easier for companies to deploy a CRM. You don't have to stand up these massive servers anymore. It's cloud based. So it was clear to us that that was going to be the new stack and we knew that you had to build a fundamentally different technology to be able to operate in that stack. And it's not just about visibility, it's about making use of collective information as well because you're going from a private environment with your own data center, your own private network, your own application stack to something that's sitting in the cloud which is a shared environment going over the internet which is the same network that carries cat videos that your kids watch. It's carrying production traffic now for your core applications. And so you need a different technology stack and you need to really sort of benefit from this notion of collective intelligence of knowing what everybody sees together as one view. So I'm curious, I think Salesforce was such an important company in terms of getting enterprises to trust a SaaS application for really core function which is sales, right? I think that was a significant moment in moving the dial. Was there a killer app for you guys that was for your customers, the one where they finally said, wait, we need a different level of visibility to something that we rely on that's coming to us through an outside service? So it's interesting, right? When we started the company, we had a lot of advisors that said, hey, your position should be you're going to help enterprises enforce SLAs with Salesforce. And we actually took a different position because what we realized was Salesforce did all the right stuff on their data centers, but the internet could mess things up or enterprise companies that were not ready to move to cloud, didn't have the right architectures would have some bottlenecks in their own environment because they're backhauling traffic from their London office to New York and then exiting from New York, they're going back to London. So all this stuff, right? So we took the position of really presenting 1,000 eyes as a way to get transparency into this ecosystem. And we believe that if we take this position of we want to help both sides, not just the enterprise company, we want to help Salesforce, we want to help enterprise companies and just really present it as a means of finding a common truth of what is actually going on. It works so much better. So there wasn't really sort of one killer application, but we found that anything that was real time. So if you think about video based applications or any sort of real time communications based so the WebExes of the world, they were just very sensitive to network conditions and internet conditions, same with things that are moving a lot of data back and forth. So these applications like Salesforce, Office 365, WebEx, they just are demanding applications on the infrastructure. And even if they run great, if the infrastructure doesn't, it doesn't give you a great experience. Right. And you guys made a really interesting insight too. It's in all your literature. It's really a core piece of what you're about. And when you own it, you could diagnose it and hopefully you could fix it or call somebody else to fix it. But when you don't own it, it's a very different game. And as you guys talk about, it's really about finding the evidence so everyone's not pointing fingers back and forth, A, to validate where the actual problem is and then to also help those people fix the problem that you don't have direct control of. So it's a very different kind of requirement to get things fixed when they have to get fixed. Yeah. And the first aspect of that is visibility. So as an example, right? You generally don't have a problem going from one part of your house to another part of your house because you own the whole place. You know exactly what sits between the two rooms that you're trying to get to. You don't run into surprises. But when you're going from, let's say, Palo Alto to San Francisco and you have two options, you can take the 101 or 280. You need to know what you expect to see before you get on one of those options, right? And so the internet is very similar. You have these environments that you have no idea what to expect. And if you don't see that with the level of granularity that you would in your own environments, you would make decisions that you have, you know, you have no control over. So the visibility is really important, but it's giving that lens, like making it feel like a Google Maps of the internet that gives you the power to look at these environments, like it's your private network. That's the hard part. Right. And then so what you guys have done, as I understand, is you've deployed sensors basically all over the internet, all at important pops and important public clouds and important enterprises, et cetera, so that you now have a view of what's going on it. I can have that view inside my enterprise by leveraging your infrastructure. Is that accurate? Correct. And so this is where the notion of being able to set up this sort of data collection environment is really difficult. And so we have created all of this over years. So enterprise companies, consumer companies, they can leverage this infrastructure to get instant results. So there's zero implementation involved. Right. But the key to that is also understanding the internet itself. And so this is where our research background comes in play because we studied, we did years of research on actually modeling the internet. So we know what strategic locations to put these probes at to give good coverage. We know how to fill the gaps. And so it's not just a numbers game, it's how you deploy them, where you deploy them. And knowing that connectivity we've created this massive infrastructure now that can give you eyes on the internet. And we leverage all of their data together. So if let's say hypothetically, AT&T has an issue, that same issue is impacting multiple customers through all our different measurements. So it's like Waze. If you're using Waze to get from point A to point B, if Waze was just used by your family members and nobody else, it would give you completely useless information, right? So the value is in that collective insight. Right. And then now you also will start to be able to leverage ML and AI and having all that data and apply just more machine learning to it to even better get out in front of problems, I imagine, as much as to be able to identify. So that's a really interesting point, right? So the first thing we have to tackle is making a complex data set really accessible. And so we have a lot of focus into essentially getting insights out of it, using techniques that are smarter than the brute force techniques to get insights out and then present it in manners that it's accessible and digestible. And then as we look into the next stages, we're going to bring more and more things like learning and so on to take it even further. Right. It's funny the accessible and digestible piece. I was just at a presentation the other day and there was a woman from a CISO at a big bank. And she talked about the problem of false positives. And in early days, their biggest issues was just too much data coming in from too many sensors and too many false positives to basically bury people so they didn't have time to actually service the things that are a priority. So a nice presentation of a whole lot of data makes a big difference to make it actionable. It is absolutely true. And the example I'll give you is oftentimes when you think about companies that operate with a strong network core like we do, they're in the weeds, right? Which is important, but what is really important is tying that intelligence to business impact. And so the entire product portfolio we've built, it's all about business impact user experience and then going into connecting the dots of the network side. So we've seen some really interesting events. And as much as we know the internet, every day I wake up and I see something that surprises me, right? We've had customers that have done migrations to cloud that have gone horribly wrong, right? So the latest one I was troubleshooting with a customer was where we saw they migrated from their on-prem data center to Amazon and the user experience was 10x worse than what it was on their own data center. Once they moved to Amazon. And what had happened there was the whole migration to Amazon included the smart CDN where they were fronting your traffic at local sites, but the traffic was going all over the place. So if a user was in London, instead of going to the London instance of Amazon, they were going to Atlanta, they were going to Los Angeles. And so the whole migration created a worse user experience. And you don't have that lens because you don't see that internet portion of that. And that's what we caught it instantly and we were able to showcase that, hey, this is actually a really bad migration. And it's not that Amazon is bad, it's just it's been implemented incorrectly. So you have to fix these things. And those are all configurations. There's all configurations. Which is so funny. All the issues you hear about with Amazon often go back to misconfiguration, mis-setting, suboptimal, leaving something open. So to have that visibility makes a huge impact. And it's more challenging because you're trying to configure different components of this environment, right? So you have a cloud component, you have the internet component, your own network, you have your own firewalls. And you used to have this closed environment. Now it's hybrid, it involves multiple parties, multiple skill sets. So a lot of things can really go wrong. The other thing I think that you guys crystallize very cleanly is kind of the inside out and outside in approach. Both A, as a service consumer, right? I'm using Salesforce, I'm using maybe S3, I'm using these things that I need. And I want to focus on that and I want to have a good experience. I want my people to be able to get on their Salesforce account and book business. But don't forget the other way, right? Because as people are experiencing my service that might be connecting through and aggregating many other services along the way. I got to make sure my customer experience is big. And you guys kind of separate those two things out and really make sure people are focusing on both of them. Correct, and it's the same technology but you can use that for your production services which are revenue generating or you can use that for your employee productivity. The visibility that you provide is across a common stack. But on the production side, for example, because of the way the internet works, right? Your job is not just to ensure a great performance in user experience, your job is also to make sure that people are actually reaching your site. And so we've seen several instances where because of the way internet works, somebody else could announce that they're Google.com and they could suck a bunch of traffic from the internet. And this happens quite routinely in the notion of what is now known as BGP hijacks or sometimes DNS hijacks. And the one that I remember very well is when there was this small ISP in Nigeria that announced the identity or the address block for Google. And that was picked up by China Telecom which was picked up by a Russian telco. And now you have Russia, China and Nigeria in the path for traffic to Google which is actually not even going to Google. So those kinds of things are very possible because of the way the internet works. How fast do those things kind of rise up and then get identified and then get shut off? Is this hours, days, weeks and this kind of example? So it really depends because if you're, let's say you were Google in this situation, right? You're not seeing a denial of service attack to your data centers. In fact, you're just not seeing traffic coming in because somebody else is taking it away. So it's like identity theft, right? Like somebody takes your identity. You wouldn't get a mail in your inbox saying, hey, your identity has been taken by XYZ. You have to find it some other way. And usually it's the signal by the time you realize that your identity has been stolen, you have a nightmare ahead of you. All right, so you've got some specific news. Great conversation. You know, it's super insightful to talk to people that are in the weeds of how all this stuff works. But today you have a new announcement, some new offerings to tell us about what's going on. So we have a couple of announcements today and coming back to this notion of the cloud being your new data center, the internet your new network, right? Two things we're announcing today is one, we're announcing our second version of the cloud benchmark performance comparison. And what this is about is really helping people understand the nuances, the performance differences, the architecture differences between Amazon, Google, Azure, IBM cloud and Alibaba cloud. So as you make decisions, you actually understand what is the right solution for me from a performance architecture standpoint. So that's one, it's a fascinating report. We've found some really interesting findings that surprised us as well. And so we're releasing that. We're also touching on the internet component by releasing a new product, which we call as internet insights. And that is giving you the power to actually look at the internet more holistically like you own the entire internet. So that is really something we're all excited about because it's the first time that somebody can actually see the internet, see all these connections, see what is going on between major service providers and feel like you completely own the environment. So are people using information like that to dynamically kind of reroute the way that they handle their traffic, or is it more just kind of a general health, kind of health overview? How much of it do I have control over? How much should I have control over it? How much of I just need to know what's going on? So it's not just me. Great question. So the best way I can answer that is what I heard CIO say in a CIO forum we were presenting at where they were a customer. It's a large financial services customer. And somebody asked the CIO what was the value of 1,000 eyes? And the way he explained it, which was really fascinating was phase one of 1,000 eyes when we started using it was getting rid of technical debt because we would keep identifying issues which we could fix, but we could fix the underlying root cause. So it doesn't happen again. And that just cleared the technical debt that we had made our environment much better. And then we started to optimize the environments to just get better, get more proactive. So that's a good way to think about it. When you think about our customers, most of the times they're trying to just not have their hair on fire. That's the first step. Once we can help them with that, then they go on to tuning, optimizing and so on. But knowing what is going on is really important. For example, if you're providing a dot com service like cube.com, it's live. And you're providing it from your data center here. You have two upstreams like AT&T and Verizon is having issues, you can turn off that connection and let all your customers back live having a full experience if you know that's the issue. The remediation is actually quite a few times it's very straightforward if you know what you're trying to solve. So do you think on the internet insights this is going to be used just more for better remediation? Or do you think it's kind of a step forward and getting a little bit more proactive and a little bit more prescriptive and getting out ahead of the issues? Or can you, because of these things, are kind of ephemeral and come and go? So I think it's all of the bow, right? So one of the things that the internet insights will help you is with planning because as you expand into new geos, so if you're a company that's launching a service in a new market, that immediately gives you a landscape of who do you connect with, where do you host? Because now you can actually visualize the entire network. How do you reach your customer base the best? So that's the planning aspect. And if you plan right, you would actually reduce a lot of the trouble that you see. So we had this customer of ours that was deploying SD-WAN, software-defined WAN, in their Asia offices. And they used Thousand Eyes to evaluate two different ISPs that they were looking at. One of them had this massive time of day congestion. So every time, every day at nine o'clock, the latency would get doubled because of congestion. It's common in Asia. The other did not have time of day congestion. And with that view, they could implement the entire SD-WAN on the ISP that actually worked well for them. So planning is important part of this. And then the other aspect of this is the thing that folks often don't realize is internet is not static. It's constantly changing. So AT&T may connect to Verizon this way. It connects it differently. It connects to somebody else. And so having that live map as you're troubleshooting customer experience issues. So let's say you have customers from China that are having a ton of issues all of a sudden. Or you see a drop of traffic from China. Now you can relate that information of where these customers are coming from with a view of the health of the Chinese internet and which specific ISPs are having issues. So that's the kind of information merger that simply doesn't happen today. Right. Well, Moe, it's a fascinating discussion. We could go on and on and on. But unfortunately, we do not have all day. But I really like what you guys are doing. The other thing I just want to close on, which I thought was really interesting is, a lot of talk about digital transformation. We always talk about digital transformation. Everybody wants to digital transformize it. But you really boil it down into really three critical places that you guys play, the digital experience in terms of what the customers experience, getting to cloud, everybody wants to get to cloud. Someone can argue how much and what percentage, but everybody's going to cloud. And then as you said in this last example, the modern way as you connect all these remote sites and you guys have a play in all of those places. So whatever you thought about in 2010, I think that it worked out pretty well. Thank you. And we had a really strong vision, but kudos to the team that we have in place that has stretched it and really made the most out of that. So excited. Well, good job. And thanks for stopping by sharing the story. Thank you for hosting. Always fun to be here. Absolutely. All right. Well, he's Moe and I'm 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.