>> Announcer: From Hell's Kitchen in New York City. It's theCUBE, on the ground, at Serverlessconf. Brought to you by SiliconANGLE Media. >> Hi, I'm Stu Miniman, here with theCUBE at Serverlessconf 2017 in New York City, Hell's Kitchen, actually, happy to welcome to the program, hard to believe, someone, as far as I can tell, we've never had on the program-- >> Yeah, I don't think so. >> But I've known for a long time, actually been drinking with him in Hell's Kitchen before, so Aneel Lakhani, thanks so much for letting me interview you. Your current position is vice president of marketing at Honeycomb.io >> Correct. >> Do you just call it Honeycomb or-- >> We just call it Honeycomb. >> Alright. So, Aneel, how are you doing? Tell us a little bit about your background, but keep it short and what gets you involved in the whole serverless ecosystem? >> Yeah, sure. So, about me, I've been in tech for a little over 20 years now, started out as an engineer, moved through a bunch of systems roles, architecture roles, and product roles, and now I run marketing at start-ups, which is what I've been doing for the last half decade or so. >> I think back to when Amazon announced Lambda, everybody's like, "Ooh, it's cool, what is it? "How do I use it?" Things like that. One of the things I've heard out of this event, this week, is tooling, monitoring, understanding, digging into it, which really falls into Honeycomb space. >> Yeah, I mean, it sort of does. I mean, at Honeycomb we do what we call observability, which is something a bit larger than just monitoring, right. It's really getting to the point where you can develop an understanding of what your services and what your code do in real life under real load with real users. >> Speaking of John Willis, about what is the role of operations when I don't own the infrastructure, I have to trust someone else to do it. So, bring us in there a little bit, what are some of the challenges people are having, how do they help when they're leveraging? >> Yeah, so something that's very clear about serverless approaches to building things, and especially if you're using something like Lambda, is that, as a software engineer, who writes a function, you are 100% responsible for all of your operations at that point, because the ops people for your stack are behind an API. You are on the other side of that API, and what they do is effectively a black box, which means you have to not only understand what your thing does, you have to understand what they do and how they do it, and it's some means of accessing both those bits of data. So you get what Amazon tells you for Lambda, or what any of the other providers tell you for their functions, but you also have to then understand how your code performs on that specific provider, which means you have to do things like wrap your functions in timers and emit events which go into Kinesis, or wherever else, so that you can track what's going on. >> Yeah, one of the problems, of course, any time you have any layer of abstraction is, if things go wrong, how do you get the expertise to know, how do you get in there, is this even worse in serverless? >> Yes and no, I mean, it depends on how much faith you have in your provider, right? So, one of the companies here put up a chart that shows you the performance, on average, of the call response time for the functions for all of the providers that provide serverless infrastructure. And they're not even remotely consistent. They're not consistent within even a few percentiles. In other words, if you care about performance, and you care about predictability for your function, it's basically impossible to get that from any given provider. >> Alright, so, talk to us, what are you hearing from users these days, what's exciting you in this space? >> Yeah, so what we hear from our users, anyway, at Honeycomb, who are using Lambda, and using serverless functions, is that the ability for them to get visibility into how a function performs is basically the highest priority outside of writing a function itself. Because they don't know what's happening below them, they don't know all the resource allocations at any given point in time by the provider, so the thing they have to go on, for the rest of the black box, is how their own function performs, which means they need the ability to take any given function and either decompose it into parts, which have their own events or metrics or telemetry that they emit, or they need to do that to the entire function from end-to-end. So basically have a concept of, this is an old concept for us, which is an end-to-end check, right? I want to know what happens when a point that I touch with a sim until my entire set of functions are complete at the end. >> Yeah, we're going back to like an IP ping, right? >> That's right, yeah, effectively. >> Today, Honeycomb, do you only support Lambda, do you support some of the other serverless frameworks that are out there? >> So, we are agnostic. So, basically, the way Honeycomb works is that our users instrument their code, and we're not service-only, it could be any code running anywhere, and they emit data, and that data is in the form of structured events, those structured events are consumed by Honeycomb, and then Honeycomb turns around and lets you do fast analysis against it. >> Yeah, you've got a lot of background of, "How do we leverage the knowledge of the crowd?" >> Yeah. >> So many times it's what are people finding when they're really getting involved here, you're tooling and others, what mistakes are they making, how can they get better, faster at what they're doing? >> Yeah, a common mistake that people make is not thinking about what is and is not blocking within their functions, and not understanding the threading model of the underlying stack, and when they should spin up additional functions and split up work, versus when they shouldn't, and the only way to understand that is, one, to read all the damn docs, and two to experiment. >> Yeah. What about the maturity of serverless? There've been a lot of discussions here. I had Mark from Trendade on, we talked about security, and the like, but what do you see, kind of in the maturation cycle, of serverless, anything you've heard, or still things that are looking to get fixed even more? >> Maturity isn't the word that I want to use here, I think it's more interesting to think of it in terms of breadth of capabilities, right? So, all of the serverless offerings for all of the vendors have limitations on either the programming languages you can use or the nature of the functions that can be run or the research allocation you can have. I think there's not a lot of maturity that we're going to see from the vendors other than more consistent performance, what we are going to see maturity in is, from the users' standpoint, of how they construct things. >> Yeah. Any data you can share is just how prevalent serverless is out there in the wild, you know, what's the typical use taste, typical customer kind of order of magnitude, how many people are doing it, and therefore driving discussions? >> Yeah, I have no idea. >> You have no idea about this. >> What I do know is, in our user base, we have some significant users of Honeycomb who are 100% run on Amazon Lambda, but that's my tiny, little sample size. >> Okay, want to give you the final word, serverless conference and serverless in general, what's your take today, what should people be looking at in the next six or 12 months? >> Yeah, so I more-or-less agree with Simon Wardley about this, which is, effectively this is a way for Amazon to eat most of the tech ecosystem, assuming people become dependent on it. >> Alright, well, I always say with theCUBE we like to take those hallway conversations, someone that I've had many hallway conversations with, and over the Twitters, and other ways, it's great to catch up with you, Aneel Lakhani, thanks so much for joining us >> Thank you so much. >> I'm Stu Miniman and thanks for watching theCUBE.

(thoughtful electronic music) >> From theCUBE studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> Enterprise applications are an enormous market, and they're enormously important to organizations globally. Essentially, the world's businesses are running on enterprise applications. Companies' processes are wired into these systems, and the investments that they make in people, process, and technology are vital to these companies' success. But it's complicated because many of these systems are decades old. Markets have changed, but the ERP system for example fundamentally hasn't. Hello everyone, and welcome to this week's Wikibon CUBE Insights, powered by ETR. This week, we're going to do a data download on the enterprise software space, and put forth some themes in our thesis around this very important segment. I'd like to do a shout-out to my friend Sarbjeet Johal, who helped me frame this segment, and he's a strategic thinker and he shared some excellent insights for this episode. What I'd first like to do is let's lay out the scope of what we're going to talk about today. So we're going to focus on the core enterprise apps that companies rely on to run their businesses. Talkin' about the systems of record here, the ERP, the financial systems, HR, CRMs, service management we'll put in there. We may touch on some of the other areas, but this is core that we're going to drill into. This is a big, big market. Customers spend many hundreds of billions of dollars in this area, you could argue about a half a trillion. And it's a mature market, as you'll see from the data. Look, it's good to be in the technology business today. This business is doing better than most, and within the technology business, it's better to be in software because of the economics and scale. And if you have a SaaS cloud model, it's even better. But the market, it is fragmented, not nearly as much as it used to be, but there are many specialized areas where leaders have emerged. ServiceNow and ITSM or Workday and HCM are good examples of companies that've specialized and then exploded, first as we saw ServiceNow blow past Workday's valuation. It was nearly 2x at one point. Now, that was before Workday crushed its earnings this week. It's up 15% today. ServiceNow took a slight breather earlier this month, but it's up on Workday sympathy today. Salesforce also beat earnings, and of course replaced Exxon Mobile on the DOW Industrials, can you imagine that? But let's bring it back to this digital transformation that you hear about. This is the big cliche from all the tech companies and especially software players. Now a lot of this DX, I sometimes call it, is related to old systems. It's especially true for the mega-caps like Oracle, SAP, PeopleSoft, JD Edwards, and even Microsoft. Take ERP and some of the mature products for example, like Oracle R12, or SAP R3 or R4. Many of these systems were put in place 15 years ago, and yeah, they're going to need to transform. They are burnt in. They were installed in what, 2005? It was before the iPhone, before social media, before machine learning and AI made its big comeback, and before cloud. These systems were built on the 1.0 of cloud. The businesses have changed but the software really hasn't. It happens every 10 to 15 years, companies have to upgrade or re-implement their systems, and optimize for the way business now runs, because they had to be more competitive and more agile. They can't do it on their old software. And God help you if you made a bunch of custom modifications. Good lucking tryin' to rip those out. And this is why pure play companies in the cloud like ServiceNow and Workday have done so well. They're best-of-breed and they're cloud, and it sets up this age-old battle that we always talk about, best-of-breed versus integrated suites. So let's bring in some of the other themes and feedback that we get from the community. Now we've definitely seen this schism play out between on-prem and cloud plays. And that's created some challenges for the legacy players. People working remotely has meant less data center, less on-prem action for the legacy companies. Now, they have gone out and acquired to get to the cloud and/or they've had to rearchitect their software like Oracle has done with Fusion. But think about something like Oracle Financials. Oracle is tryna migrate them to Fusion, or think about SAP R3, with R4, SAP pushing HANA. All this is going to cloud-based SaaS. So the companies that've been pure play SaaS are doing better, and I say quasi-modern on this slide because Salesforce, ServiceNow, Workday, even Coupa, NetSuite which is now Oracle, SuccessFactors which SAP purchased, et cetera, these are actually pretty old companies, the earlier part of the 2000s or in the case of Salesforce, 1999. And you're seeing some really different pricing models in the market. Things are moving quickly to an OPEX model. You have the legacy perpetual pricing, and it's giving way to subscriptions, and now we even see companies like Datadog and Snowflake with so-called consumption-based pricing models, priced as a true cloud. And we think that that's going to eventually spill into the core SaaS applications. Now one of the concerns that we've heard from the community is that some of the traditional players that were able to hide from COVID earlier this year might not have enough deferred revenue dry powder to continue to power through the pandemic, but so far the picture continues to look pretty strong for the software companies. We'll get into some of that. Now, finally, this is a premise that I talked to Sarbjeet about, the disruption perhaps comes from cloud and developer ecosystems. Y'know I remember John Furrier and I had a conversation awhile back with Jerry Chen from Greylock. It was on theCUBE, and it was kind of like, went like this. People were talking about whether AWS was going to enter the applications market, and the thesis here is no, or not in the near future. Rather, the disruptive play, and this is really Sarbjeet's premise, is to provide infrastructure for innovation, and a PaaS layer for differentiation, and developers will build modern cloud-native apps to compete with the SaaS players on top of this. This is intriguing to me, and is likely going to play out over the next decade, but it's going to take a while, because these SaaS players are, they're very large, and they continue to pour money into their platforms. Now let's talk about the shift from CAPEX to OPEX and bring in some ETR data. Of course, this was well in play pre-COVID, but the trend has been accelerating. This chart shows data from the August ETR survey, and it was asking people to express their split between CAPEX and OPEX spend, and as you can see, the trend is clear. Goes from 48% last year, 55% today, and moving to over 62% OPEX a year from now. It's no surprise, but I think it could happen even faster depending on the technical debt that organizations have to shed. And hence, the attractiveness again of the SaaS cloud players. So now let's visualize some of the major players in this space, and do some comparisons. Here we show one of our favorite views, and what we're doing here is we juxtapose net score on the vertical axis with market share on the horizontal plane. Remember, net score is a measure of spending momentum. Each quarter, ETR asks buyers, are you planning to spend more or less, and they essentially subtract the lesses from the mores to derive net score. Market share on the other hand is a measure of pervasiveness in the dataset, and it's derived from the number of mentions in the sector divided by the total mentions in the survey, and you can see each metric in that embedded table that we put in there. So I said earlier, this was a pretty mature market and you can see that in the table. Eh, kind of middle-of-the-road net scores with pretty large shared ends, i.e. responses in the dataset, but a lot of red. There are some standouts, however, as you see in the upper right, namely, ServiceNow and Salesforce. These are two pretty remarkable companies. ServiceNow entered the market as a help desk or service management player, and has dramatically expanded its TAM, really to the point where they're aiming at $5 billion in revenue. Salesforce was the first in cloud CRM, and is pushing 20 billion in revenue. I've said many times, these companies are on a collision course, and I stand by that, as any of the next great software companies, and these are two, are going to compete with all the mega-caps, including Oracle, SAP, and Microsoft, and they'll bump into each other. Which brings us to those super-cap companies. You see Microsoft with Dynamics, they show up like they always do. I'm like a broken record on Microsoft. I mean they're everywhere in the survey data. Now Oracle and SAP, they've been extremely acquisitive over the years, and you can see some of their acquisitions on this chart. I've said many times in theCUBE that Larry Olsen used to denigrate his competitors for writing checks instead of code, but he saw the consolidation trend happening in the ERT, ERP space before anyone else did, and with the $10 billion PeopleSoft acquisition in 2005, set off a trend in enterprise software that did a few things. First, it solidified Oracle's position further up the stack. It also set Dave Duffield and Aneel Bhusri off to create a next-generation cloud software company, Workday, which you can see in the chart has a net score up there with ServiceNow, Salesforce, and Coupa, and it also led to Oracle Fusion Middleware, which is designed as an integration point for all these software components, and this is really important because Oracle is moving everything into its cloud. And you can see that its on-prem net score, which puts it deep into negative territory. Now SAP, take a look at them, they have much higher net scores than Oracle, and you can see it's acquired SaaS properties like Ariba, Concur, and SuccessFactors, which have decent momentum. But you know, SAP, and we've talked about this before, is not without its challenges. With SAP, HANA is the answer to all of its problems. The problem is that it's not necessarily the answer to all of SAP's customers' problems. Most of SAP's legacy customers run SAP on Oracle or other databases. HANA is used for the in-memory query workload, but most customers are going to continue to use other databases for their systems of record. So this adds complexity. But HANA is very good at the query piece. However, SAP never did what Oracle did with Fusion, which as you might recall, took more than a decade to get right. HANA is SAP's architectural attempt to unify the SAP portfolio and get, (laughs) really get off of Oracle, but it's many years away, and it's unclear when or if they'll ever get there. All right, let's move on. Here's a look at a similar set of companies, but I wanted to show you this view because it gives you a detailed look at ETR's net score approach, and it tells us a few things more. And remember, this is a survey of almost 1,200 technology buyers. That's the N, that's the respondent rate. So this chart shows the net score granularity for the enterprise players that we were just discussing. Let me explain this. Net score is actually more detailed than what I said before. It comprises responses in four categories. The lime green is new adoptions. The forest green is growth in spending of 6% or more, the gray is flat spend, the pink is a budget shrink of 6% or greater, and the red is retiring the platform. So what this tells us is that there's a big fat middle of stay the same. The lime green is pretty small, but you can see, NetSuite jumps out for new adoptions because they've been very aggressive going after smaller and mid-sized companies, and Coupa, the spend management specialist, shows reasonably strong new adoptions. Now ServiceNow is interesting to me. Not a ton of new adoptions. They've landed the ship and really penetrated larger organizations. And while new adoptions are not off the charts, look at the spending more categories, it's very very strong at 46%. And the other really positive thing for ServiceNow is there's very little red. This company is a beast. Now Salesforce similarly, not tons of new adoptions, but 40% spend more. For a company that size, that's pretty impressive. Workday similarly has a very strong spending profile. At the bottom of the chart, you see a fair amount of red, as we saw on the XY graph. But now, let's take another view of net score. Think of this as a zoom in, which takes those bar charts but shows it in a pie format for individual companies. So we're showing this here for ServiceNow, Workday, and Salesforce, and we've superimposed the net score for these three in green, so you can see ServiceNow at 48%, very good for a company headed toward five billion. Same with Workday, 40% for a company of similar size, and Salesforce has a comparable net score, and is significantly larger than those two revenue-wise. Now this is the same view, this next chart's the same view for SAP and Oracle, and you can see substantially lower than the momentum leaders in terms of net score. But these are much larger companies. SAP's about 33 billion, Oracle's closer to 40 billion. But Oracle especially has seen some headwinds from organizations spending less which drags its net score down. But you're not seeing a lot of replacement in Oracle's base because as I said at the top, these systems are fossilized and many are running on Oracle. And the vast majority of mission-critical workloads are especially running on Oracle. Now remember, this isn't a revenue-weighted view. Oracle charges a steep premium based on the number of cores, and it has a big maintenance stream. So while its net score is kind of sucky, its cashflow is not. All right, let's wrap it up here. We have a very large and mature market. But the semi-modern SaaS players like Salesforce and ServiceNow and Workday, they've gone well beyond escape velocity and solidified their positions as great software companies. Others are trying to follow that suit and compete with the biggest of the bigs, i.e. SAP and Oracle. Now I didn't talk much about Microsoft, but as always they show up prominently. They're huge and they're everywhere in this dataset. What I think is interesting is the competitive dynamics that we talked about earlier. These kind of newer SaaS leaders, they're disrupting Oracle and SAP, but they're also increasingly bumping into each other. You know, ServiceNow has HR for example, and they say that they don't compete with Workday, and that's true. But y'know, these two companies, they eye each other and they angle for account control. Same thing with Salesforce. It's that software mindset. The bigger a software company gets, the more they think they can own the world, because it's software, and if you're good at writing code and you see an opportunity that can add value for your customers, you tend to go after it. Now, we didn't talk much about M&A, but that's going to continue here, especially as these companies look for TAM expansion and opportunities to bring in new capabilities, particularly around data, analytics, machine learning, AI and the like, and don't forget industry specialization. You've seen Oracle pick up a number of industry plays and as digital transformation continues, you'll see more crossing of the industry streams because it's data. Now, the disruption isn't blatantly obvious in this market right now, other than SaaS clouds going after SAP and Oracle, and it's because these companies are deeply entrenched in their customer organizations and change is risky. But the cloud developer, the open source API trend, it could lead to disruptions, but I wouldn't expect that until the second half of this decade as cloud ecosystems really begin to evolve and take hold. Okay, well that's it for today. Remember, these Breaking Analysis episodes, they're all available as podcasts wherever you listen so please subscribe. I publish weekly on Wikibon.com and SiliconANGLE.com, so check that out, and please do comment on my LinkedIn posts. Don't forget, check out ETR.plus for all the survey action. Get in touch on Twitter, I'm @dvellante, or email me at David.Vellante@siliconangle.com. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching everybody. Be well, and we'll see you next time. (thoughtful electronic music)

(energetic music) >> Live from Orlando, Florida, it's theCUBE covering .conf 18, brought to you by Splunk. >> We're back in Orlando, Splunk .conf 2018, I'm Dave Vellante, Stu Miniman, and this is theCUBE, the leader in live tech coverage. Doug Merritt is here, the CEO of Splunk, long time CUBE guest, great to see you again. >> Thank you, Dave, great to be here. >> So, loved the keynote yesterday and today. You guys have a lot of fun, I was laughing my you-know-what off at the auditions. They basically said, Doug wasn't a shoo in for the keynote, so they had these outtake auditions. They were really hilarious, you guys are a lot of fun. You got the great T-shirts, how do you feel? >> It's been a, my favorite time of year is .conf, both because there's usually so much that we're funneling to our customers at this time, but being here is just infectious, it's, and one of the things that always amazes me is it's almost impossible to tell who are the customers and who are the employees. That just, I think Devonia this morning said it's a family affair, and it's not just a family affair, it's that there's a shared passion, a shared, almost culture and value set, and there's, it just is a very inspiring and naturally flowing type of event and I know I'm biased because I'm the CEO of Splunk, but I don't, I just don't know of events that feel like our, like .conf does. There's a lot of great shows out there, but this has got a very unique feel to it. >> Well, we do a lot of shows, as you know, and I've always said, .conf, I think ServiceNow, does a great job obviously, re-invent the tableau shows. That energy is there, and the other thing is, we do, when we go to these shows, a lot of times, you'll look at the keynotes and say, are there any products being announced? You guys, that wasn't a problem here. You guys announced this -- >> Not this year. >> Bevy of products, I mean, it's clear the R and D is translating into stuff that people can consume, and obviously that you can sell, so that's huge. >> I'm really excited about the product roadmap right now, and it's, that was, when I got the job, almost three years ago, one of the key areas I leaned forward and the board was excited about it was, what, where or how are we going to take this product beyond the amazing index and search technology that we have? And this show, it takes a while to progress the roadmap to the point that you can get the type of volume that we have here, but this show was the first time that I felt that we had laid enough of the tracks, so you could see a much, much broader landscape of capabilities, and now it's a challenge of packaging and making sure our customers are successful with it, with the product that we just have, the products we've announced. >> Cloud caught a lot of companies and a lot of end user companies, flatfooted. You guys have embraced the cloud, not only with the AWS partnership, which we're going to talk about, but also the business model. You're successfully transitioning from a company with perpetual license model, to a ratable model, which is never easy. Wall Street is killing companies who try to do that. Why have you been successful doing that? You know, give us an update. >> Yeah, so five years ago, less than 20% of our contracts were, had any type of subscription orientation to it, whether it's a multi-year term or a cloud. We'd just launched our cloud four years ago. And we moved from there to we had told the street there would be 65% term in subscription by the end of this year and updated guidance at the end of the second quarter, which is just a month and change ago, that we've already hit the 75% mark that we were set in for next year, so it's been a pretty rapid progression and I think there're two elements that have helped us with that. One: cloud continues to catch fire and so the people's orientation on "Do I do something in the cloud?" four years ago they were much more nervous, so less nervous today. But data is growing at such a huge rate and people are still wrapping their heads around, "How do I take advantage of this data, how do I even begin to collect this data and then how do I take advantage of it?" And the elasticity that comes in the cloud and that comes with term contracts, we can flex out and flex back in, I think it's just a much more natural contracting motion than you bought this big, perpetual thing and pay maintenance on it, especially when someone is growing as fast as data is growing. >> Well and it requires you to communicate differently to the financial analysts. >> It does. >> Obviously, billings, you know, was an important metric. You've come up with some new metrics to help people understand the real health of the business. And one of the other metrics that strikes me, and you see this with some of the successful companies, I actually think Aneel Bhusri was sort of the modern version of this, is the number of seven figure deals. You're startin' to hit that, and it's not, the way he's phrased it was pretty good. It's not something you're trying to engineer, it's the outcome -- >> Yes. >> of having great, loyal customers, it's not something you try to micromanage. >> Right, and that's, just recently we dropped six figure deals, which, when I joined, you got this wonderful dynamic forecasting system that sits on top of sales for us, and so as head of sales, where I started, you're really paying attention to deals. I'd go down to a hundred thousand dollar deals that would track throughout the quarter. And now it's hard to get it down to the six figures 'cause we've got a big enough envelope of seven figure deals. So the business has changed pretty dramatically from where it was, but it is an outgrowth of our number one customer priority, which is, or number one corporate priority, which is customer success. 'Cause that investment by companies, when you get to a million dollars plus, in most cases that's a million annually, you better believe in and trust that vendor, 'cause that's no longer an easy, small departmental sale. You're usually at the CIO, CFO type level. So it's something that we're very honored by, that people trust us enough to get that footprint of Splunk to be that size and to feel like they're getting a value from Splunk to justify that purchase. >> Alright we'll get off the income statement, Stu, and you can read about all that stuff, and we're going to get into, we've got a lot of ground to cover with you, Doug. Jump in here, Stu. >> Yeah, so Doug, I've really enjoyed talking to some of your customers that, you know, most of them started on premises with you and now many of them, they're using Splunk cloud, it's really kind of a hybrid model, and it's been really interesting to watch the maturation of your partnership with Amazon, and being the leader in the cloud space. Give us a little bit of color as to what you're hearing from the customers, you said three, four years ago, you know, they were obviously a little bit more cautious around it, and bring us inside a little bit that partnership. >> Sure, so the first piece that, as part of Splunk, that I think is a little bit different than other vendors is because we are both a lower level infrastructural technology, right, data is, the way I frame what we do is there's these raw materials, which are all these different renditions of data around, and companies increasingly have to figure out how to gather together these different raw materials, put them together different ways, for the output that is driving their business. And we are the manufacturing parts provider that makes it easy for them to go and pick up any of these different compounds and then actually do what they want to do, which is make things happen with data. And that middle layer is really important and we have never taken a super strong stance either, we started on prem, but as we moved to cloud, we never took a strong stance saying everything should be in the cloud or everything should be on prem because data has gravity, there is physics to data. And it doesn't always make sense to move data around and it doesn't always make sense to keep data stagnant, so having that flexibility, being able to deploy your collection capability, whether it's ours or third party, your storage capability, and then your process and your search, what are you going to do with the data, anywhere that makes sense for a customer, I think, is important. And that's part of that hybrid story, is as people increasingly trust and interview us and other cloud vendors to build core apps and then house a lot of their data, we absolutely need to be there. And I think that momentum of the cloud is certainly as secure and, in many cases, more secure than my on prem footprint, and the velocity of invention that some like ABDS is driving allows me to be much more agile and effectively drive application development and leading edge capability, I think just has people continuing to trust the cloud service providers a little bit more. >> Yeah well, we're here in the pavilion, and seeing your ecosystem grow, we've been at re:Invent for about five years, that ecosystem is just so >> It's been amazing. >> massive and full, give us a little bit about the relationship with Amazon and how you look at that, how Amazon looks at a company like yours. >> Yeah, it's been, so one, whenever you're playing with a highly inventive and hugely successful company like Amazon, my orientation and what I convey back to the company is our job is to be more inventive, more agile, and continue to find value with our maniacal focus every day being the data landscape. Data is a service and outcomes is a service, so our job is run faster than Amazon. And I think that this show and our announcements help illustrate that our invention cycle is in high tilt gear and for what we do, we are leaning in in a really aggressive way to add that value. With that backdrop, Andy and I formed this partnership four years ago. He felt there's enough value in Splunk and we were a good enough partner and the way we consume their services that he would commission and quota their sales reps whenever a Splunk sale was done in the ADBS landscape, which I think has been really helpful for us, but we obviously are a huge customer of ADBS's and they become an increasingly large customer of ours and finally gave us approval with their three year renewal a quarter ago to publicly reference them as a sizeable customer for us. >> Oh, okay, congratulations on that. And something I've really, it's really crystallized for me: so many administrators out there, you look at their jobs, you know, what are they? It's like okay, I'm the security expert, I'm the network certified person. You're really, your users here, you know, they are the beacons of knowledge, they are the center of data, is really what they are. You know, Splunk's a tool, they're super excited about the product, but it's data at the center of what Splunk does and therefore, you're helping them in just such a critical aspect of what is happening in the industry today. >> Yeah, the key aspects of the keynote, of my keynote, were we are moving to a world where data is the product that people care about so the whole object is how do you make things happen with data and the people that can get that done increasingly are becoming the most valuable players on the field, so what infrastructure, what tooling, what capability exists that allows people from all departments, you know, we're very heavy within IT and security, but increasingly HR departments, finance departments, marketing departments, sales departments, manufacturing departments will not be successful without a really competent group of folks that understand how to make things happen with data and our job is to lower that bar so you don't have to go to Carnegie Mellon for four years and get a Masters in Computer Science and Data Science to be able to be that most valuable person on the field. >> I want to take a moment, I want to explain why I'm so bullish on Splunk. We had a conversation with Susan St. Ledger yesterday. Digital transformation is all about data. >> Yup. >> And you guys are all about data, there's the cliche which is "data is the new oil" and we've observed, well not really. I could put oil in my car, I can put oil in my house, I can't put it in both places, but data? I can use that same data in a lot of different use cases and that's exactly what you guys are doing now as you expand into line of business -- >> Yup. >> With Splunk Next. >> Yup. >> So you've announced that, you showed some cool demos today. I'd like you to talk about how you're going from your core peeps, the IT ops guys and the sec ops guys, and how, what your plan is to go to lines of business. More than just putting the data out there, you've come up with some new products that make it simpler, like business work flows, but what else are you doing from a go to market standpoint and a partnership standpoint, how do you see that playing out? >> Yeah, I think that the innovation on product, there are three key pillars that we're focusing on. Access data, any type of data, anywhere it lives. Make sure that we're driving actionable outcomes with that data, and acquisitions like Phantom and VictorOps have been a key pillar of that, but there's other things we're doing. And then, expand the capability of finding those outcomes to a much broader audience by lowering the bar. So the three key themes across the portfolio. But all of those are in service of the developers at a customer site, the developers in the ecosystem, to make it easier for them to actually craft a set of solutions that help a retailer, help a discrete manufacturer, help a hospital actually make things happen with data. 'Cause you could certainly start with a platform and build something specific for yourself but it's much easier if you start with a solution. And a lot of the emphasis we've been putting over the past two to three years is how do we up that platform game. And the many, many, 20 different product announcements that we rolled at this .conf and one of them that I'm also very excited about is our developer cloud where we've really enhanced the API layer that interacts with the different services that the entire Splunk portfolio represents. Not just the search and index pieces that people are familiar with but everything from orchestration to role based access to different types of visualization so a very broad API layer that's a well-mannered, restful set of APIs that allows third parties to much more crisply develop, excuse me, applications to compliment the 1800 apps that are already part of our Splunk base and right behind me is a developer pavilion where we've got the first hand full of early adopter OEM partners that are building their first sets of apps on top of that API framework. >> Dozens of them, it's actually worth walking around to see. Now, so that developer cloud is a lever, those developers are a lever for you to get into lines of business and build those relationships through the software, really, and through the apps. Same thing for IOT. >> Yup. >> Industrial IOT. Now, we've observed, and a lot of the IT companies that we see are trying to take a top down approach into IOT and we don't think it's going to work. It's, we talk about process engineers, it's operations technology people, they speak a different language. It's not going to be a top down, here, IT. >> A very different audience. >> It's going to be a bottoms up set of standards coming from the OT world. The brilliance of what you guys have, it's the data, you know, it's data coming off machines, data, you don't care. And so, you're in a good position to do a bottoms up in IOT and we heard some of that today. Now, there are some challenges. A lot of that data is still analog, okay, you can't really control that. A lot of the devices aren't instrumented, they're not connected, you can't control that. But once they become instrumented and connected and that analog data gets digitized, you're in a really good position, but then you got to build out the ecosystem as well. >> Yup. >> So talk about how you're addressing some of those challenges in industrial IOT. >> Yup, man, it's a great subject 'cause I think that the trying to rely on standards is the wrong approach. The velocity across this digital landscape is so high and my view over the past 30 years, I think it's only accelerated now, is there's going to be more and more varieties of data with different formats than there's ever been, and we've seen it in the past five years. Just look at the variety of services on top of AWS, which didn't even exist ten years ago, but and they now have hundreds of services and there is no organizing principle across those services as far as data definition. So it's a very chaotic data landscape and I don't think there's any way to manage it other than to embrace the chaos and work a little bit more bottoms up, you know, grab this data, don't worry about cleansing it, don't worry about structuring it, just make sure you have access to it and then make sure that you've got tools like Splunk that allow you to play with the data and try and find the patterns and the value inside of that data, which is where I think we're very uniquely suited as a technology set. Helping the ecosystem come to that realization is a key aspect of what we're doing. We're trying to attack it the same way we attacked the IT security piece which is pick a handful of verticals and really focus on the players, both the marquis anchor tenants, the BMWs, the Siemens', the Deutsche Bahn railroads of the world, as customers. And through that, get access to the key influencers and consultants and advisors to those industries and start to get that virtuous circle of "I actually have more data than I think I have." Even though there's some analog machines, there's so many different ways to attach to the signal that those machines are emitting and it may not be bi-directionally addressable, but at least you can see what's happening within those machines without a full manufacturing floor rip and replace. And everyone is excited about doing that. The advisors to the industry are excited, the industry themselves are excited. We had BMW on stage who walked through how they're using Splunk to help on everything from product design all the way through to predictive maintenance and feedback on the quality of the cars that they're rolling out. We've all heard stories that there's more lines of code in the Ford F150 and these other vehicles than there is within Facebook right now, so we all are dealing with rolling and sitting in building's and house's data centers. How do you make sure that you're able to pay attention what's happened within that data center? So I think that that is as big or bigger of an opportunity than what we've done with IT and security, it just has its own pace of understanding and adoption. >> Carnival Cruise Line, another one, Stu. We had those guys on today and they basically look, they have a lot of industrial equipment on those ships, so they're excited. >> Yeah, absolutely. Alright, so Doug, we started the beginning talking about the last couple years, how we measure Splunk has changed. Going to more subscription models, talk about how many customers you have. I look at developers, I look at IOT, whole different set of metrics. So if you look at Splunk Next, how do we measure you, going forward? What is success for your team and your customers going forward? >> Yeah, and the whole orientation around Splunk Next, as I'm sure Susan covered, it's not a product, it's a messaging framework. People are so used to Splunk being all about the collection of data within the index and searching in said index, and we're increasingly moving, we're complementing the index, the index is a incredibly unique piece of IP for us. But there's a lot of other modalities that can complement what that index does and Splunk Next represents all of our investments in next generation technologies that are helping in with everything from stream processing to distributed compute capability, next generation visualizations, et cetera. The metric that I care about over time is customer adoption and customer success. How many use cases are being deployed at different customers? How many companies, both customers and partners, are incorporating Splunk in what they do every day? You're getting OEM Splunk, making Splunk a backbone of their overall health and success. And ultimately that needs to translate into revenue, so revenue and bookings will always be a metric that we care about, but I think the leading indicators within theses different markets of rate of adoption of technology and, more importantly, the outcomes that they're driving as they adopt this technology, are going to be increasingly important. >> Yeah, I just have to tell you, when you talk about your customers not only excited, but it's a deeper partnership when you talk to insurance company out of Toronto that, like, they're talking to the people that they insure about, should they be using Splunk and how do they do that. It just, a much deeper, and you know, deeper than a partnership model for your customers. >> It's one of the things I love about this conference, is it's, we were talking about earlier, it's hard to tell the customers from the employees, like, there's a, there's a, this whole belief and purpose that everybody shares, which I adore about being here. But when you look at a sea of data, we've thought traditionally looked at the data we manufacture, typically data that's historic and at rest from our ERP systems. This next wave is certainly all the data that's happening within our organizations but increasingly it's all the data that's available in the world at large. And whether it's insurance or automotive or oil and gas, the services that I'm going to have to deliver to customers require me to farm data outside of my walls, data inside my walls, combine those two, to come up with unique value added services for my customers. So it's great to hear that, that our customers are on that journey 'cause that's where we all need to go to be successful. >> And there's a definitely alignment there. Doug, I know you're super busy, we got to go. Thanks so much for coming on theCUBE. Give you the last word, .conf 18 takeaways. >> (laughs) Unbelievable excitement and enthusiasm. A huge array of products that, I think, broaden the aperture of what Splunk does so dramatically that people are really trying to digest, "What should, how should I be thinking about Splunk moving forward?" And I'm, we started a whole series of transformations three years ago, and I'm really excited that they're all starting to land and I can't wait for the slow realization of the impact that our customers are counting on us to provide and that we'll increasingly be known for across the data landscape. >> Well and the landscape is messy and, as you said, the messiest part of that landscape is the data landscape. You guys are helping organize that, curate it. And hopefully we're helping curate some of the, from some of the noise and distracting to the signal to you on theCUBE. Doug, thanks so much for coming on theCUBE, great to see you again. >> Thank you Dave, thank you Stu, you guys do a great job. >> Thanks, we appreciate that. >> Thanks for being here with us. >> Alright, keep it right there, buddy. We'll be back with our next guest from .conf 18 from Orlando, we'll be right back. (digital music)

(upbeat music) >> Live from Orlando, Florida, it's theCUBE covering .conf18. Brought to you by Splunk. >> Hello everybody, welcome to Orlando. This is theCUBE, the leader in live tech coverage, and we're here at Splunk conf .conf 2018. The hashtag is #splunkconf18. My name is Dave Vellante, I'm here with my co-host Stu Miniman. Stu it's great to be in Orlando again. Last year we were in D.C. This is our seventh year covering Splunk.conf and we've seen the company really move from essentially analyzing log files on PRAM in a perpetual license model, to now a company that is permeating all of IT into the lines of business. Security, IT performance, application performance, moving into IOT. Really becoming a mature company. It's a company with $1.7 billion in revenue forecasted for this year. They were talking about a $17 billion market cap, they're growing at 36%, and they're a company Stu, that is in the process of successfully going from a perpetual license model to a renewable model. Splunk set the goal of being 75% renewable by 2020. Sounds like renewable energy, but repeatable renewable from a subscription standpoint, they're already there. So you're seeing that in the execution. This is your first .conf, or conf as they like to say. We were at the ESPN Wide World of Sports Center, you saw what, what's the number, 8,000 people? >> Yeah I think 8,000 at the show this year, it's strong growth, and Dave I've been hearing from the team for years the excitement of the show, the passion of the show, saw like, right over near where we were sitting there's the whole group of that was the Splunk trust. They've got the fezzes on, a lot of them have superhero capes on, and it's what you'd expect from a passionate, technical maybe even geeky audience. Things like, we're announcing the S3 API-compatible storage. Everybody's like, yay we're so excited for this. It's hardcore techies. >> What was the other big clap? Screen? >> Yeah, that's right dark mode. We're going to go to dark mode, I don't have to play with the CSS. Anybody that's played with a website, changing these things is not trivial. I click a little button and the joke was this was the bright one for the executives, but when I'm down in the gamer center I don't want this glaring screen here, so I can switch it over to dark mode. And people were pretty excited about that. >> So again the roots of Splunk, they took log data and analyzed it. Doug Merritt the CEO, talked today talked about, making things happen with data. I thought he did a really good job of laying out the past, putting the past behind us in terms of he said, "I've been to I can't tell you "how many Master Data management classes "trying to optimize the database, "trying to codify business processes "and harden those business processes." The problem is data is messy. Data is growing so fast, business processes are changing so fast, the competition is moving so fast, customers are changing. So you have to be able to organize your data in the moment. So, the whole idea that, even go back to the early big data days and Hadoop, the whole idea was to bring five megabytes of compute to a petabyte of data. And no schema on write, or what some call schema on read. Splunk was really a part of that. Put the data, get the data organized in a way that you can look at in in a moment, but then let the data flow. So that has definite implications in terms of how you think about data. It's not trying to get the data all perfect so you can use it, it's trying to get the data into your data ocean, as we like to say, and then have the tooling to be able to analyze it very, very quickly. They announced Splunk 7.2 today which is a big deal. Some things, we'll talk about a few of the features, obviously focused on performance, but one of the things they talked about was basically being able to split storage and compute. So previously you had to add essentially a brick of storage and compute simultaneously. We've heard about these complaints for years in the conversion infrastructure space, it's obviously a problem in the software space as well. Now customers are able to add storage or compute in a granular fashion, and they're cozying up to Amazon doing S3 compatible store. >> Dave, I love that message that he put out there you said, "life is messy. "You can't try to control the chaos, "you want to be able to ride those waves of data "take advantage of them and not overly "make things rigid with structure." Because once you put things in place you're going to get new data or something else that's going to come along and your structure is going to be blown away. So when you need to search things you want to be able to look at them in that point in time but be able to ride those waves, flow with the data, live the way your data lives. That's definitely something that resonates in this community. Dave, something I've watching this space, as an infrastructure guy and watching the Cloud movement, there were a lot of reasons why traditional big data failed. I kind of never looked at Splunk like most of those other big data companies. Yes they had data, yes they're part of the movement of taking advantage of data, but they weren't, oh well we have this one tool that we're going to create to do it all, like some of the new players. They're playing with all the latest things. You want tentraflow, you want to do the A.I, the ML. Splunk is ready to take advantage of all of these new waves of technologies, and they've done a couple of acquisitions like VictorOps in the space that they keep growing and the goal is, you mentioned the revenue, but Splunk today has I think it's 16,000 customers. They have a short term goal of getting to 20,000 but with what they started talking about in the keynote today, Splunk Next, they really want to be able to do an order of magnitude of more customers and when you get great customer examples like Carnival Cruises. The CEO I thought, talked about the sea of data. Lots of good puns in the keynote there but mobile cities floating around and lots of data that they want to be able to get the customer experience and make sure the customer gets what they need and make sure that Carnival knows what they have to make sure that they're running better and optimizing their business too, so great example. Looking forward to talking to them on theCUBE. >> Well and they have many dozens, I think it's in last quarter, it was like 60 plus deals over a million dollars. They have many $10 million plus deals. That's an outcome of happy customers, it's not like they're trying to engineer those deals. I'm sure some of the sales guys would love to do that. But that's a metric that I think was popularized by the likes of Aneel Bhusri at Workday, certainly Frank Slootman at ServiceNow. It's one that Wall Street watches and Splunk it's an indicator. Splunk is doing some very very large deals that underscores the commitment that many customers are making to Splunk. Having said that, there are many more that are still smaller users of Splunk. There's a lot of upside here. And they're going into a serious TAM expansion that's something we're going to talk to Doug Merritt about. Making acquisitions of a company, VictorOps was their most recent acquisition sort of security orchestration and management. They're doing, the ecosystem is growing, they're doing bigger deals or partnerships with the likes of Accenture, Deloitte is here, EY. Accenture actually has a huge space at this event, and those are indicators. I want to go back to something you said earlier about the failure of big data. Certainly big data failed to live up to the hype in many ways. You didn't see a lot of wholesale replacement of traditional databases and EDWs. You did see a reduction in cost, that was the big deal. But clearly enterprise data warehouses and ETL, they're still a fundamental part of people's data strategies despite what Doug Merritt saying, hey, the data is messy and you've just got to let it flow, essentially what he's saying. There is still a need for structured data and mixing, sort of, interacting of structured and unstructured data. Bringing transaction data and systems of intelligence together, analytic data. But the one thing that big data did do and the Hadoop movement, it did a couple things: one is, architecturally it pushed data out and back in the day you had to get a big Unix box and stuff everything in there. It was your god box of data. And you had Oracle licenses and Sun Microsystems boxes and it was very expensive. And you had a couple of people who knew how to get the data out. So the goal of democratizing data, what it did is, it is messy. Data went out to the distributed nodes and now the edge. But it brought attention to the importance of data and the whole bromide of data driven companies. And so now we're in a position to make a new promise and that promise is A.I, machine learning, machine intelligence, which seems to be substantive. We talk a lot on theCUBE is this old wine, new bottle? And we had an event in New York last month and the consensus from a lot of practitioners and others in the room was: no there's something substantive, the data substrate is now in place. Now it's all about taking advantage of it. Tooling is still complex but emerging or evolving. And I think the cloud, to your point, is a huge part of that. By integrating data pipelines in the cloud it dramatically simplifies the deployment model and the complexity of managing big data. >> Yeah, Dave, as you said, there used to be these giant boxes and some of these initiatives I needed 18 months, you know, millions of dollars and a large time you either need to be a country or a multi-national company to be able to put this thing together. I remember one of the earliest case studies that David Floyer did when we were looking at big data it was how do I take that 18 month deployment and drive it down to more like a six week deployment, and when you talk about A.I, ML, and deep learning, the promise is that a business user should be able to get answers in a much much shorter window. So actionable on that data, being able to do things with it not just looking backwards but hear the team. So I want to be able to be proactive, I want to be able to be responsive. I want to even predict what my client is going to need and be ready for it. >> So as Doug Merritt said that digital and physical worlds they're coming together. They don't stop evolving. They're organic. Your data model has to be flexible. It's a sea of data. It's an ocean of data. It's not a confined data lake, as John Furrier and others like to say. And so I was happy to hear Doug Merritt talking about a sea. We use the term oceans because that's really what it is. And oceans are unpredictable, they're sometimes really harsh, they can sometimes be messy. But they're constantly evolving and so I think that kind of metaphor works in this world of Splunk. We've got two days here of coverage. A lot of customers coming on today, in fact, Splunk is one of those companies that puts many customers on theCUBE, which we love. We love to dig in to the case studies. We've got some ecosystem partners. Some of the big SIs are coming on and of course, we're going to hear from some of the product people at Splunk that go to market people. Doug Merritt will be on tomorrow. And a number of folks. I'm Dave Vellante, @DVellante on Twitter. He's @Stu. Stu Miniman. Keep it right there, buddy. We'll be back with our next guest right after this short break. You're watching day one from Splunk conf18 in Orlando. Be right back. (soft bouncy music)

>> Hey, welcome back everybody. Jeff Rick here with the Cube. We are live in downtown San Jose at the historic Pagoda Lounge, part of Big Data SV, which is part of Strata + Hadoop Conference, which is part of Big Data Week because everything big data is pretty much in San Jose this week. So we're excited to be here. We're here with George Gilbert, our big data analyst from Wikibon, and a great guest, Gaurav Dhillon, Chairman and CEO of SnapLogic. Gaurav, great to see you. >> Pleasure to be here, Jeff. Thank you for having me. George, good to see you. >> You guys have been very busy since we last saw you about a year ago. >> We have. We had a pretty epic year. >> Yeah, give us an update, funding, and customers, and you guys have a little momentum. >> It's a good thing. It's a good thing, you know. A friend and a real mentor to us, Dan Wormenhoven, the Founder and CEO of NetApp for a very long time, longtime CEO of NetApp, he always likes to joke that growth cures all startup problems. And you know what, that's the truth. >> Jeff: Yes. >> So we had a scorching year, you know. 2016 was a year of continuing to strengthen our products, getting a bunch more customers. We got about 300 new customers. >> Jeff: 300 new customers? >> Yes, and as you know, we don't sell to small business. We sell to the enterprise. >> Right, right. >> So, this is the who's who of pharmaceuticals, continued strength in high-tech, continued strength in retail. You know, all the way from Subway Sandwich to folks like AstraZeneca and Amgen and Bristol-Myers Squibb. >> Right. >> So, some phenomenal growth for the company. But, you know, we look at it very simply. We want to double our company every year. We want to do it in a responsible way. In other words, we are growing our business in such a way that we can sail over to cash flow break-even at anytime. So responsibly doubling your business is a wonderful thing. >> So when you look at it, obviously, you guys are executing, you've got good products, people are buying. But what are some of the macro-trends that you're seeing talking to all these customers that are really helping push you guys along? >> Right, right. So what we see is, and it used to be the majority of our business. It's now getting to be 50/50. But still I would say, historically, the primary driver for 2016 of our business was a digital transformation at a boardroom level causing a rethinking of the appscape and people bringing in cloud applications like Workday. So, one of the big drivers of our growth is helping fit Workday into the new fabric in many enterprises: Vassar College, into Capital One, into finance and various other sectors. Where people bring in Workday, they want to make that work with what they have and what they're going to buy in the future, whether it's more applications or new types of data strategies. And that is the primary driver for growth. In the past, it was probably a secondary driver, this new world of data warehousing. We like to think of it as a post-modern era in the use of data and the use of analytics. But this year, it's trending to be probably 50/50 between apps and data. And that is a shift towards people deploying in the same way that they moved from on-premise apps to SAS apps, a move towards looking at data platforms in the cloud for all the benefits of racking and stacking and having the capability rather than being in the air-conditioning, HVAC, and power consumption business. And that has been phenomenal. We've seen great growth with some of the work from Microsoft Azure with the Insights products, AWS's Redshift is a fantastic growth area for us. And these sorts of technologies, we think are going to be of significant impact to the everyday, the work clothing types of analytics. Maybe the more exotic stuff will stay on prem, but a lot of the regular business-like stuff, you know, stuff in suits and ties is moving into the cloud at a rapid pace. >> And we just came off the Google Next show last week. And Google really is helping continue to push kind of ML and AI out front. And so, maybe it's not the blue suit analytics. >> Gaurav: Indeed, yes. >> But it does drive expectations. And you know, the expectations of what we can get, what we should get, what we should be moving towards is rapidly changing. >> Rapidly changing, for example, we saw at The New York Times, which as many of Google's flagship enterprise customers are media-related. >> Jeff: Right. >> No accident, they're so proficient themselves being in the consumer internet space. So as we encountered in places like The New York Times, is there's a shift away from a legacy data warehouse, which people like me and others in the last century, back in my time in Informatica, might have sold them towards a cloud-first strategy of using, in their case, Google products, Bigtable, et cetera. And also, they're doing that because they aspirationally want to get at consumer prices without having to have a campus and the expense of Google's big brain. They want to benefit from some of those things like TensorFlow, et cetera, through the machine learning and other developer capabilities that are now coming along with that in the cloud. And by the way, Microsoft has amazing machine learning capability in its Azure for Microsoft Research as well. >> So Gaurav, it's interesting to hear sort of the two drivers. We know PeopleSoft took off starting with HR first and then would add on financials and stumble a little bit with manufacturing. So, when someone wants to bring in Workday, is it purely an efficiency value prop? And then, how are you helping them tie into the existing fabric of applications? >> Look, I think you have to ask Dave or Aneel or ask them together more about that dynamic. What I know, as a friend of the firm and as somebody we collaborate with, and, you know, this is an interesting statistic, 20 percent of Workday's financial customers are using SnapLogic, 20 percent. Now, it's a nascent business for them and you and I were around in the last century of ERP. We saw the evolution of functional winners. Some made it into suites and some didn't. Siebel never did. PeopleSoft at least made a significant impact on a variety of other things. Yes, there was Bonn and other things that prevented their domination of manufacturing and, of course, the small company in Walldorf did a very good job on it too. But that said, what we find is it's very typical, in a sense, how people using TIBCO and Informatica in the last century are looking at SnapLogic. And it's no accident because we saw Workdays go to market motion, and in a sense, are following, trying to do the same thing Dave and Aneel have done, but we're trying to do the same thing, being a bunch of ex-Informatica guys. So here's what it is. When you look at your legacy installation, and you want to modernize it, what are your choices? You can do a big old upgrade because it's on-premise software. Or you can say, "You know what? "For 20% more, I could just get the new thing." And guess what? A lot of people want to get the new thing. And that's what you're going to see all the time. And that's what's happening with companies like SnapLogic and Workday is, you know, someone. Right here locally, Adobe, it's an icon in technology and certainly in San Jose that logo is very big. A few years ago, they decided to make the jump from legacy middleware, TIBCO, Informatica, WebMethods, and they've replaced everything globally with SnapLogic. So in that same way, instead of trying to upgrade this version and that version and what about what we do in Japan, what do we do in Sweden, why don't you just find a platform as a service that lets you elevate your success and go towards a better product, more of a self-service better UX, millennial-friendly type of product? So that's what's happening out there. >> But even that three-letter company from Walldorf was on-stage last week. You can now get SAP on the Google Cloud Platform which I thought was pretty amazing. And the other piece I just love but there's still a few doubters out there on the SAS platform is now there's a really visual representation. >> Gaurav: There is. >> Of the dominance of that style going up in downtown San Francisco. It's 60 stories high, and it's taken over the landscape. So if there's ever any a doubt of enterprise adaptation of SAS, and if anything, I would wonder if kind of the proliferation of apps now within the SAS environment inside the enterprise starts to become a problem in and of its own self. Because now you have so many different apps that you're working on and working. God help if the internet goes down, right? >> It's true, and you know, and how do you make e pluribus unim, out of many one, right? So it's hilarious. It is almost at proliferation at this point. You know, our CFO tapped me the other day. He said, "Hey, you've got to check this out." "They're using a SAS application which they got "from a law firm to track stock options "inside the company." I'm like, "Wow, that is a job title and a vertical." So only high growth private venture backed companies need this, and typically it's high tech. And you have very capable SAS, even in the small grid squares in the enterprise. >> Jeff: Right, right. >> So, a sign, and I think that's probably another way to think about the work that we do at SnapLogic and others. >> Jeff: Right, right. >> Other people in the marketplace like us. What we do essentially is we give you the ERP of one. Because if you could choose things that make sense for you and they could work together in a very good way to give you very good fabric for your purposes, you've essentially bought a bespoke suit at rack prices. Right? Without that nine times multiplier of the last century of having to have just consultants without end, darkened the sky with consultants to make that happen. You know? So that, yes, SAS proliferation is happening. That is the opportunity, also the problem. For us, it's an opportunity where that glass is half-full we come in with SnapLogic and knit it together for you to give you fabric back. And people love that because the businesses can buy what they want, and the enterprise gets a comprehensive solution. >> Jeff: Right, right. >> Well, at the risk of taking a very short tangent, that comment about darkening the skies, if I recall, was the battle of the Persians threatening the 300 Greeks at the battle of Thermopylae. >> Gaurav: Yes. >> And they said, "We'll darken the skies with our arrows." And so the Greek. >> Gaurav: Come and get 'em. >> No, no. >> The famous line was, he said, "Give us your weapons." And the guy says, "Come and get 'em." (laughs) >> We got to that point, the Greek general says, "Well, we'll fight in the shade." (all laughing) But I wanted to ask you. >> This is the movie 300 as well, right? >> Yes. >> The famous line is, "Give us your weapons." He said, "Come and get 'em." (all laughing) >> But I'm thinking also of the use case where a customer brings in Workday and you help essentially instrument it so it can be a good citizen. So what does that make, or connect it so it can be a good citizen. How much easier does that mean or does that make fitting in other SAS apps or any other app into the fabric, application fabric? >> Right, right. Look, George. As you and I know, we both had some wonderful runs in the last century, and here we are doing version 2.0 in many ways, again, very similar to the Workday management. The enterprise is hip to the fact that there is a Switzerland nature to making things work together. So they want amazing products like Workday. They want amazing products like the SAP Cloud Suite, now with Concur, SuccessFactors in there. Some very cool things happening in the analytics world which you'll see at Sapphire and so on. So some very, very capable products coming from, I mean, Oracle's bought 80 SAS companies or 87 SAS companies. And so, what you're seeing is the enterprise understands that there's going to be red versus blue and a couple other stripes and colors and that they want their businesspeople to buy whatever works for them. But they want to make them work together. All right? So there is a natural sort of geographic or structural nature to this business where there is a need for Switzerland and there is a need for amazing technology, some of which can only come from large companies with big balance sheets and vertical understanding and a legacy of success. But if a customer like an AstraZeneca where you have a CIO like Dave Smoley who transformed Flextronics, is now doing the same thing at AstraZeneca bringing cloud apps, is able to use companies like SnapLogic and then deploy Workday appropriately, SAP appropriately, have his own custom development, some domestic, some overseas, all over the world, then you've got the ability again to get something very custom, and you can do that at a fraction of the cost of overconsulting or darkening the skies in the way that things were done in the last century. >> So, then tell us about maybe the convergence of the new age data warehousing, the data science pipeline, and then this bespoke collection of applications, not bespoke the way Oracle tried it 20 years ago where you had to upgrade every app tied into every other app on prem, but perhaps the integration, more from many to one because they're in the cloud. There's only one version of each. How do you tie those two worlds together? >> You know, it's like that old bromide, "Know when to hold 'em. "Know when to fold them." There is a tendency when programming becomes more approachable, you have more millennials who are able to pick up technology in a way. I mean, it's astounding what my children can do. So what you want to do is as a enterprise, you want to very carefully build those things that you want to build, make sure you don't overbuild. Or, say, if you have a development capability, then every problem looks like a development nail and you have a hammer called development. "Let's hire more Java programmers." That's not the answer. Conversely, you don't want to lose sight of the fact that to really be successful in this millennium, you have to have a core competence around technology. So you want to carefully assemble and build your capability. Now, nobody should ever outsource management. That's a bad idea. (chuckles) But what you want to do is you want to think about those things that you want to buy as a package. Is that a core competence? So, there are excellent products for finance, for human capital management, for travel expense management. Coupa just announced today their for managing your spend. Some of the work at Ariba, now the Ariba Cloud at SAP, are excellent products to help you do certain job titles really well. So you really shouldn't be building those things. But what you should be doing is doing the right element of build and buy. So now, what does that mean for the world of analytics? In my view, people building data platforms or using a lot of open source and a lot of DevOps labor and virtualization engineering and all that stuff may be less valuable over time because where the puck is going is where a lot of people should skate to is there is a nature of developing certain machine language and certain kind of AI capabilities that I think are going to be transformational for almost every industry. It is hard to imagine anything in a more mechanized back office, moving paper, manufacturing, that cannot go through a quantum of improvement through AI. There are obviously moral and certain humanity dystopia issues around that to be dealt with. But what people should be doing is I think building out the AI capabilities because those are very custom to that business. Those have to do with the business's core competence, its milieu of markets and competitors. But there should be, in a sense, stroking a purchase order in the direction of a SAS provider, a cloud data provider like Microsoft Azure or Redshift, and shrinking down their lift-and-shift bill and their data center bill by doing that. >> It's fascinating how long it took enterprises to figure out that. Just like they've been leveraging ADP for God knows how many years, you know, there's a lot of other SAS applications you can use to do your non-differentiated heavy lifting, but they're clearly all in now. So Gaurav, we're running low on time. I just want to say, when we get you here next year, what's top of your plate? What's top of priorities for 2017? Cause obviously you guys are knocking down things left and right. >> Thank you, Jeff. Look, priority for us is growth. We're a growth company. We grow responsibly. We've seen a return to quality on the part of investors, on the part of public and private investors. And you know, you'll see us continue to sort of go at that growth opportunity in a manner consistent with our core values of building product with incredible success. 99% of our customers are new to our products last quarter. >> Jeff: Ninety-nine percent? >> Yes sir. >> That says it all. >> And in the world of enterprise software where there's a lot of snake oil, I'm proud to say that we are building new product with old-fashioned values, and that's what you see from us. >> Well 99% customer retention, you can't beat that. >> Gaurav: Hard to beat! There's no way but down from there, right? (laughing) >> Exactly. Alright Gaurav, well, thanks. >> Pleasure. >> For taking a few minutes out of your busy day. >> Thank you, Jeff. >> And I really appreciate the time. >> Thank you, Jeff, thank you, George. >> Alright, he's George Gilbert. I'm Jeff Rick. You're watching the Cube from the historic Pagoda Lounge in downtown San Jose. Thanks for watching.