 Okay, welcome everyone to the Cube Conversation here in Palo Alto in the Cube Studio in Palo Alto, California. I'm John Furrier, the founder of Silicon Angle. We rod bagged the VP of customer support at Nimble. Congratulations for your great launch you had. We are at the Cube there. Great to have you back for a drill down on conversation. Thank you. One of the things that we talked about was the success of the company you guys had and the event you guys had was fantastic. It's really fun to see a company do so well with the product and being public too, which is hard with all the scrutiny. And the customer support is a big deal and validation around product market fit is a big one. So the topic here is gonna be InfoSight, the management tool. Talk about that product and why that's playing such a big role in this new storage ecosystem, this new platform around the data. Yeah, so I think in our case it's, what we realized early was that there was an opportunity to really collect a lot of data from the systems and really provide that back to customers in a different way, something more than just raw data where they had to interpret it themselves, but where we could provide the analytics and real actionable events and recommendations back to them. So that's really become something now that our customers are absolutely dependent on managing their environment. And I think as you, as the environment gets more and more complex than the applications do and there's more and more demands on the storage environment, that you just need that transparency. And a lot of our customers will tell us that in other storage devices they've used in the past, they really haven't had that kind of transparency and it's really kind of a mystery to them. So we've really opened that up and just become transparent in that way. You know, one of the things we love talking with theCUBE is the folks in the trenches doing all the work and the cloud certainly has been a transformative market. And so I want you to talk about the dynamic around the cloud, because now that we use into some of the things that are transforming in the market, certainly management is critical, across platforms, across different devices. What is the big thing about the cloud that customers are coming to you saying, this is changing the game for me or this is what I need? Yeah, so from the infocyte perspective in the cloud and being able to manage those devices from the cloud, the big, I think, advantage we have by doing it that way and not having an on-premise solution is that when we understand storage and we understand how it's supposed to work, how our product is supposed to work and what's optimal in an environment. So to be able to do the analytics and deploy it literally to all of our customers one night because we've changed something within infocyte in the cloud, all of those customers can take advantage of that day. So it makes for deployment, makes for us doing very complex analytics when the horsepower takes to do that in the cloud infrastructure rather than having to have that on-premise. So it allows us fast deployments, very deep analytics capabilities through the horsepower and providing that in the cloud that we can do. All right, so I'm a customer. I'm like, okay, every storage room is pumping their management. What makes you guys so different here? Yeah, so I guess the bottom-liner, in my opinion, the real key is the deep data that we actually collect from the devices. So right from the beginning, right from day one, we had this infrastructure within the product that we call the stats library that literally sends us back each day, somewhere anywhere from 30 to 100 million data points from every array. All of that gets into an analytics database. So that, I think, really becomes the foundation of the secret sauce that we have with what we can do with InfoSight to interpret all of this data, see a whole bunch of correlations across what's happening in the storage, what's happening on the network and the host and so on, and really, again, achieving that very deep analytics and pushing it back to the customer in meaningful ways, not just a bunch of stats. So it's talking to Suresh about the culture of your company, and you guys have a can-do attitude. You work hard, play hard, and you've got a lot of pride. And, but still, small company relatives are the giants out there, okay? You guys are public, you're not tiny, you're not a startup, certainly not on the private market, which, you know, valuates are a little bit crazy right now. But the big question always is, how do you guys compete with the giants in the service side? Because service is where people are differentiating. So what are you guys doing differently, and how do you guys compete, and how do you attack that kind of stickiness or that lock-in spec with being service? Yeah, and I think it's kind of an interesting dynamic that we've seen change, you know, over the course of the last four or five years, when, you know, since we've deployed those first systems, where in the beginning it was really the question was, hey, you really are a small company, you know, they would question our viability, and they would question how can we possibly do support, you know, and compete against the big guys in really both of those dimensions, but, you know, especially on the support side, as it pertains to your question. So, you know, that was key back then. And then it was tough, but even back then, we showed them the automation. We didn't always have infocyte right at the beginning, but we still had all that data back at home. And we had a whole bunch of automation in place right from the very beginning. So, you know, that was something that, you know, we always presented in any visit with a customer, you know, really, we really led, you know, or tried to, not just with the product, but, you know, intermingled with support of that product and what we were doing on the back end. So I think we started to gain a lot of trust fairly early. The, you know, and that just grew through references, where, you know, we had a lot of feedback from customers on how well we were doing support and so on. So the question now has changed. So they still ask, you know, the financial viability is, you know, obviously off the table at this point, but, you know, now they're asking, well, we used to ask, you know, can you do support? And now they're asking, can you maintain the support you do? You know, because we've got a very good reputation with our support, the question now is, you know, can you maintain that? So we do an awful lot. At a scale level, or is there still the automation that's still a big piece? I think it's scale. You know, where's automation going and then how do you really scale the, you know, that support experience as we grow and get more and more customers? And it's kind of the same answer. It is all about automation. So we have a large team that reports directly into me in the support organization that is an engineering team and a data analytics, data scientists. So, you know, that, you know, the focus is there to really make sure that we can maintain that support capabilities as we grow and scale. So we have a whole team, you know, looking at it. You know, I love how in the old days, when the old days, even 10, 15 years ago, it was always kind of like the thing, oh, startups really can't break into the enterprise IT because track record was important and viability. Certainly, you guys are a public company now and doing extremely well, but the cloud gives you the ability to deliver things in a unique way. You guys have done that. So talk about the automation piece and provisioning. These are terms now that are becoming differentiators and quite frankly, marketing buzzwords for some companies. So how do you, as a customer, sift through the noise of, oh, everyone's got this new automation, this automatic provisioning, hybrid cloud. So again, that's what they're being bombard with this kind of fun. So how do you drill down and unpeel the reality around automation? Yeah, so I guess there's a couple of aspects. So we do a lot of automation from detecting issues. You know, if the array or the environment is not up to sort of our best practices, you know, that gets automatically detected in the site. We create automated cases with, you know, very detailed and very specific instructions back to the customer on how to solve that issue. So the automation is there and we do all sorts of health checks on the system and that's really one of our top priorities within that engineering team is how do you constantly do more and more wellness checks to make sure that that customer's environment is in optimal shape. So that kind of covers the automation piece but the kind of the provisioning and such, you know, I think that the main key point there, and we see this all the time, is that when, you know, as you're moving more and more stuff onto your storage array, you know, people buy this for one application or two applications and before you know what it's performing so well, they keep loading it up with more and more things. So the one thing that we're very transparent with that gets used constantly within InfoSight is projections on where your capacity trending is heading and when you're gonna need to add more storage but even more importantly with Adaptive Flash, when do you need to add more cash and when do you need to add additional CPU horsepower to that storage array to keep up with the growing demand that you're putting on it. And that's all very transparent and very predictive in nature. So people get those cues right from InfoSight well in advance of needing that new hardware and so on. So they can plan for those upgrades in a timely manner and so on. So customers always want control, IT or control freaks, I was on a crowd chat today talking about, you know, IT guys are like OCD when it comes to equipment there, all the details, they wanna control everything but now the old way of procuring servers have changed. You guys have proven that this notion of just buying, racking and stacking servers are a thing of the past, so certainly trending, you see the market share numbers will converge infrastructure is obviously booming. You guys made a bet on reference architectures. How has that played out from your standpoint? That was a big bet that you guys made that this was gonna move to this kind of reference architecture, how did that play out? Yeah, so I think, you know, we have, you know, our smart stack reference architecture for that environment and that's just doing incredibly well. I mean, because we, you know, we have taken those reference architectures and defined them, we test all of those within our technical marketing, you know, facilities. Well, what are we gonna, what is smart stack? Yeah, so that's our integration with Cisco UCS so that, you know, basically you have this reference architecture that is literally plug and play so that you can deploy that virtualized and environment with storage and so on in your environment in a very simple manner that's kind of pre-canned and baked and, you know, it's gonna work and, you know, you follow the best practice guides that we, our best practice recommendations that we built into that architecture so that you just, you know. And the benefits what, that eliminate support, eliminate integration, what's the, Yeah, I guess a couple of things. I mean, what, you know, if the customer, from the customer's perspective, they kind of come to one place. I mean, so if they are having an issue with that environment, they call nimble support. We can work any issue up that stack. So we have people that are very, very knowledgeable, for example, with UCS and setting that up and making sure that it's optimized not just from the storage perspective but from UCS perspective as well. So it's, you know, the one number to call, they get support up the stack. So is that competing against EMC in the net after the world? Yeah, exactly. So that's, you know, that's a direct competitor. I think we're doing extremely well in that area. It's definitely a big growing part of the, So that's a good bet. That was a good bet then for you guys. So it's working out. Oh yeah, I mean, it's essential. And I think, you know, you'll see more and more of those kind of tighter integrations, you know, coming out of nimble as we go. So who's the big winner there? The channel partner, the sales guys, the integration guys, are the customers all three? What's the net of it? I think it's all three. I mean, we do have, you know, channel partners and distributors that really are selling smart stack as a solution. So it's very easy for them to quote that whole thing and just deploy that entire solution to a customer. From a customer's perspective, they don't have to go out and buy all these constituent parts and hope they work and so on and figure, you know, call three vendors to figure out how to get them integrated and so on. So when you guys had your big event, we had theCUBE down there doing a live broadcast. One of the questions I got on Twitter after the fact was, the question I wrote it down here was, and I wanted to ask you here, is how does nimble deliver 24 by seven times 365 around the world? They wanna know specifically. You know, why do you guys do that? Yeah, so I guess one of the things that's very interesting too, and I'll take it back to InfoSight because that's sort of what I like, but because we have InfoSight and a lot of these, you know, sort of mundane or easy cases or, you know, best practice stuff is kind of taken off the table through automation, really allows us to hire as a staffing profile for our support engineers, very senior people. So we have no tiering at all within support. So when you call in, you don't get a, you know, customer service rep that kind of screens the call and directs you to the right place. Not like Comcast. Yeah, exactly. You saw that, he was going around the customer support call, but again, it's pretty seamless, pretty flat. So it's very flat structured. There is no tiering at all. When you call in and you get a support engineer, he is gonna handle that case to the end. So that's true throughout the entire world. So, and again, because we're only hiring very senior people, it is difficult to hire very senior people in California and Silicon Valley here that are gonna work through the night. I mean, you can get great top talent when they're allowed to work, you know, 8 a.m. to 5 p.m. or something. So we do have support centers around the world so that everybody more or less is working, you know, sort of regular daylight hours and it allows you to really get that top talent in the door. And it's just seamless from that perspective. So tell about the InfoSight new stuff that's around the adaptive flash messaging you guys had. Talk about specific, that was well received. Yes. This adaptive flash was really a home run. Yeah. How does that fit in? How does InfoSight fit into all that? Yeah, so I think a couple of things. So first of all, we do a lot of analytics on how the cash is being utilized and what are the working set sizes for all the different workloads. And as you know with adaptive flash, the other point of it there is you can just put any different mixed workloads on there and the right things are gonna be in cash when you need them, this sort of thing. So we do a lot of analytics to make sure that's working well. And of course, if you keep loading a lot of applications on there, you may run low on cash. And of course with adaptive flash, it's very simple just add more and take care of that. So within InfoSight, we make those predictions for customers. So we do, you know, if we see that workload increasing and the working sets are such that we want those in cash every day at 10 a.m. because we can tell that's when they're being used and you need more cash to accomplish that, then you'll see recommendations right on InfoSight. In fact, we had a couple of cases just the other day where we made those recommendations to customers that they really needed to do a cash upgrade. One was for an all flash shelf. The other one was just for an SSD upgrade. And literally the account teams, you know, reach back to support and say, hey, thanks for doing this. Got two customers sending us POs today because of these recommendations. You know, one thing I love about your company is that you guys are one, doing well, financially that's a result of the great people and also the product. But also you made some good bets. Obviously, reference architecture was one, but data analytics is another. And, you know, we love big data here at SiliconANGLE, Wikibon, we love seeing the impact of analytics. So talk about some of the things you mentioned there because you're doing some pretty cutting-edge stuff around predictive analytics. How do data analytics fit into the support experience? And what are you learning from configurations? Is all this analytics coming into your platform? Are they optimized across different user bases? Can you share some insight and color around that? Yeah, so there's a few things with that too. I mean, one of the big things that we've just released as an internal tool to our sales guys that actually also got to reseller shortly here is a sizing tool. So what we've done is basically have the data scientists look across our install base at the different kind of work profiles that we have. So we know, for example, that this set of arrays and customers are using exchange with this size of exchange database or this many mailboxes, this many SQL databases on that same array that are this size and so on. And so based on those profiles of that work, we can see, again, the working set sizes in cash and how long they need to be in there, how big those working set sizes are. And based on all of that, what we've done is develop the tool where we just ask the customer or the sales person questions about a pre-sales engagement where we say, how many SQL databases do they wanna run on this array and how big is their exchange environment? How many PDI clients do they wish to run? And from that, we can look at that based on all of the data we have from the entire install base and really actually model exactly what they're going to need based on what we've already deployed to the field. So we can make recommendations about how- So you're leveraging a lot of the data. Oh yeah, I mean, it's huge. So we can really predict exactly what kind of an array they need, how much cash, they need what, how much from the all flash shelf would they need, so on and so forth. So we can really- Do people scratch their heads like, oh my God, you guys are really doing well there because one of the things that you're doing and demonstrating is that you're breaking down the silos around our philosophies. You don't, you're not the support department. You don't have your database. The old way it was, you had your support database and paying questions, calls would come in, other product groups would have different databases, sales would have different databases. You guys bring it all together. Yeah, yeah, and I think a typical example of that that you've seen in the past is kind of the database admin guy complaining about performance, and the network guy trying to sort of help figure that out and the storage guy getting blamed for everything and no one knowing exactly where the issue is and so on and certainly the storage guy not knowing in advance that the database guy is having a performance issue. You know, with doing things like InfoSight and making that available to the administrator of the storage device, they see that stuff happening before the DBA's worrying about it or even catching it. So you know, we can make recommendations on how to improve the performance of that environment and it might be maybe the simple things like more cash, but it can be a lot more complex things where we do correlation analysis around the environment and what's happening there. We may uncover a network issue that shows up in InfoSight that allows them, you know, that storage guy is getting that alert that there's an issue that is in the network that's causing the database problems. So you can fix that with the networking. I always get the question when people see me and hey, what do you think about this company here, startup or this company's going public and I always say, you know, the common thing is, is it in a transformative market? Is it highly growth? And are they leveraging things that require, that automate and create more relevance? And you mentioned this whole thing about the database thing is, you know, the thing there is imagine the time savings. Never mind the actual health of the network and the health of the overall systems. But I don't have to basically be a database guy to get predictive database stuff or vice versa. Yeah, you know, it was funny. We had an existing customer come in for an UBC visit just because they had some new senior managers there and they wanted to understand more about Nimble. So, you know, they had kind of the head, you know, the director of IT and I think the CIO came in and so on. And we were in the EBC, you know, the executive briefing center, giving them some demos of the product and going through the product roadmap and we gave them a demo of InfoSight and we actually brought up their arrays and just to show them. And they had been having a performance issue and really it all boiled down really to them just adding more and more load. But, you know, when we brought it up in InfoSight we could just clearly see these growth patterns happening on the array from a performance perspective where they just had a couple of blips back in January and one in March and then it got worsened again in whatever June or something. So, they actually looked back on their change management and it was exactly the dates that they were adding new and new load. And in fact, we had these spikes where they added load and they backed it up because of some software issues with the build they had sort of deployed. So, you could see all of this happening and they were astonished. They were sort of battling, you know, why are they seeing slow and slow performance on a particular application and it was purely because they had, you know, turned on more and more features on that application and really hadn't used InfoSight yet to see, you know, what impact that was going to make and so on. So, they basically went away with a plan from an EBC because of how to address that. Well, we talked about this at your adaptive flash launch with Shuresh and some of your management team is that not all flash arrays are created equal. And I was just on a chat talking about flash arrays and that people love apples and oranges. Oh, you're comparing apples to oranges. There is really no killer feature or no killer spec because it's pretty much, it's a versatile environment relative to the workload. So, you know, people are being sold a bill of goods. We kill it in speed and performance. But what does that mean? So, how do you share that with customers when they say, hey, you know, I just, someone came in, sales were from another company, came in, they promised massive speeds and feeds, IOPS throughput and cost per gigabyte, or terabyte and does that mean anything? What's the new metric of flash? Can you share your thoughts there? It's a good question because, you know, back three or four years ago when I was doing training for new customers or reseller training and so on and everybody in the room, you know, it was the old math. It's like 150 IOPS per disk and therefore you needed 96 disks and, you know, we're getting the same thing out of 12. TCO calculator, all that stuff, it's old school. The whole thing is blowing out of the water. So, I mean, it's interesting. And people just, you know, still, I think even today when they first see Nimble, still have a hard time understanding, you know, how we can drive 125,000 IOPS out of, you know, essentially nine data disks. I mean, it's a lot. What's the secret sauce? What's the secret sauce? You know, I mean, it's basic. I mean, it really boils down to that log-structured file system that's CASL and it really boils down to sequential rights on disks which you can really drive them that fast. And obviously, you know, having the cash there for the reed side, I mean, that's, you know, and making sure the stuff you need is in cash when you need it. And again, that's, you know, it's kind of this pretty interesting thing when we do that sizing tool, for example, we can take a look at a SQL database that might be a terabyte big. But at any instant in time, the amount of data that actually needs to be in cash for that working set size is a fraction of that, a small fraction of it. So, you know, it's kind of not anything anybody really understood unless you have all of that data coming back. We're here with Rod Bag, VP of Customer Support at Nimble and Grade Company. And it's great to have you on because being the customer support, you get to see everything, all the scabs and all the goodness and all the support. But it's a true tell-tale sign of where you're at and good companies use the customer support aspect to really feed into product requirements, feed into better innovation. So with that, I gotta ask you, you know, what are you seeing from the field? I've seen the customers. What are you seeing from the customers in terms of happiness, the goodness, the greatness of Nimble to some of the complaints? What are the things that you guys need to do differently? Where's the hotspots? Where are the speed bumps? What do you guys need to do better? Yeah, so I think the, you know, from the speed bumps or the hotspots, you know, perspective, you know, as you said, I mean, we see a lot of, I mean, support, we see everything and we get a lot of compliments on our support. We see some of the bad stuff. I think the, not challenging again because we have very senior people, but one of the big things is looking at stuff outside of the array. And we, I mean, I firmly believe we got the array side nailed pretty darn good in all regards from the product, supportability of it and everything else. The next real sort of killer app from our perspective from the support side is really going up the stack. And we do that to some extent right now from what we collect on the array where we can see things from the host to some degree and we can certainly see network things. But the real next killer thing is really getting that same kind of detail. Kind of a, maybe adaptive stack? That's right, all the way to the stack. Maybe that's a new buzzword, I just made that up. But I mean, smart stack is kind of a telegraphing your move there, right? Yeah, smart stack is in a way. You're showing some kind of automation and some pre-referenced, pre-engineered. Yeah, so now we want to get that same data from those virtual machines, from those network. What does the latency look like from the virtual machine perspective versus our perspective? And you can do a lot of correlation analysis when you have the data right up the stack. She's moving into the machinery of IT more aggressively, relatively outside of your company. And to be honest, that's exactly what our customers want. I mean, they have become such a trusted partner with us now with InfoSight and just depend on it for everything. They really want that data all the way up. So we're starting on that and you'll see more of that coming up. Well, Rod, I got to ask you on the 24-7, 365 question earlier around your company. What's it like to work for a company that's gone public, growing like crazy, hairs on fire? What's it like working inside a company like that? You know, I give a lot of credit to the three people. I mean, the two founders, Varun and Amesh and Suresh, the CEO. I mean, they have just driven a culture that is just spectacular to work for. And everybody in there says that. I mean, you could ask anybody. They just love working. Just great guys, great management team. We have a no-jerk policy and we really have no jerks so everybody is happy there and everybody gets along. It's just a great place to be. Just love it. What's the no-jerk policy? We don't want to hire jerks. People, is it the, are you going to travel this guy kind of test it? Can you get along with him? Is that, how do you, what's the filter? Yeah, I think that is, I mean, we're fortunate enough that a lot of people at Nimble know a lot of other people at Nimble and we've, because we've had success, it's easy to attract good talent that we know from previous lives and so on. So I think everybody's got a pretty good feeling about what people are like when they come in the door and we do some, you know, some extensive interviewing process where, you know, people really sit down and chat and they chat with the founders and everything else. So I think everybody gets a pretty good feel for what people are like before they come in the door. It's, culture is pretty solid. Oh yeah. Good diversity. Yeah, great diversity, you know, around the world, I think it's working out great. You travel, you know, travel to different locations and talk to the sales guys and it's just unbelievable. Everybody's got the same attitude about the company and about how to treat customers and understanding of the product. Good culture is magical. It really is fantastic. It really makes a difference. I'm a big proponent of good culture. Hard charging, but also, you know, being inclusive and being just good human being. Yeah, yeah, exactly. Well, great, great to have you here in theCUBE conversation here at Palo Alto. Thanks for coming in, really appreciate it. This is a CUBE conversation here with Rod and John here at theCUBE, right back. Thank you.