 Live from Silicon Valley, it's theCUBE, covering Google Cloud, Next 17. Lauren, welcome to theCUBE special coverage of Google Next 2017. This is theCUBE's two days of live coverage here in Palo Alto studio. We have reporters and analysts on the ground. We have all the Wikibon analysts in San Francisco have been up there since Monday for the Google Analyst Summit, as well as reporters at the keynote. We're going to be going live to folks on the ground for a reaction commentary from the keynotes, as well as all the big breakouts and news coverage. Again, two days of live coverage and we want to put a shout out to Intel for their sponsorship and allowing us to do the two days of in-depth coverage, really breaking down the cloud and really talking about this new mega trend around cloud service providers where it's a multi-cloud game which is pretty clear that's happening and then the classification of the world with AI, machine learning, really changing the game on infrastructure, software development, this is the digital transformation, this is the made trend and here to help kick off our two days of coverage is venture capital Scott Rainey who's a partner at Red Point Ventures who has a lot of history in network, software SaaS. Scott, thanks for joining us on the kickoff here for our coverage. Yeah, the big story I was Google news is obviously Diane Greene, great executive. She gets a lot of criticism for her presentation. Some people were saying all this a little bit sleepy but she's got a folksy kind of, I called the Berkeley kind of vibe but she's super smart. She's a great cool person but she came in from VMware which has a lot of chops in the enterprise. So it's no surprise that Google cloud is now marching heavily towards the enterprise. They have all the window dressing, you're seeing all the check boxes next to the sales and marketing, some of the things that they're doing but the end of the day, it's an AI machine learning at the center of all this where data and a new cloud developer or a new developer market has been emerging very fast. They call it cloud native. You're investing in this space. Give me your thoughts on this because you guys have to look at the 20 mile stair down the road, look at kind of that five year horizon or plus for investments whether it's early stage or whatnot but you guys have done a lot with startups that have been successful. Twilio when public that you're on the board of you have a lot of investments in there that are doing very, very well. The developers, the opportunities, what's your take as an investor writing big checks? Yeah, well I think Google's a really interesting way to start this conversation not just the Google cloud platform but Google as an entity. I think Google is frankly been defining about 10 years ahead of where enterprises are in terms of how they're thinking about building and deploying applications. And so if you look at the Google, the work they've done to actually support their internal efforts, these guys then create white papers or white papers are then disseminated and then a whole set of industries get kicked off around those. So obviously one of the great examples of that is what happened around to Duke and that wave. I think what we're in the process of seeing right now is a whole series of innovations that are being developed around more kind of cloud-native technologies. I think Kubernetes is a great example which is really the outgrowth of work that Google had done around Borg. And so we spent a lot of time thinking about the work that Google's, the things that Google are working on now recognizing that's the future of enterprise computing. It takes, obviously takes a while to get there. But there have been massive initiatives. And it's transformative too. Again, I mentioned to you that they went public, great service. So it's not go public, they're now running on Google Cloud and some on AWS. There's game-changing opportunities out there that are going to come out of these unique perspectives that developers and entrepreneurs might have and say, hey, I'm going to innovate on camera technology. That becomes Snap, which becomes kind of a unique, weird app to mainstream. This is not a one-off. I mean, there's a lot happening around creative young entrepreneurs and old, some guys are age. But either way, it's not just apps, it's transformation at the network level all the way up to the top of the stack. What are the trends around that? Because machine learning is aussie hot. What are you hearing from pitches? What's coming through your door? What are you looking at? You guys see a lot of deals. What's the trends that are coming out of that? Well, every pitch we see has machine learning in it. Every company has become an AI company at some level. So that's clearly a big trend. I think for us, the way that we look at that in terms of investments is we're recognizing that the algorithms are really becoming commoditized at some level. And Google with TensorFlow is actually helping make that happen. As we just talked about democratizing machine learning at some level, the key there is data. And so when we look at these companies, we're looking for companies that have a unique proprietary access to data that they can apply those algorithms to deliver insight. I think one of the more interesting areas of applications around that we're seeing is in the SaaS space. So at this kind of upper level, the cloud space, how it's really not enough now to build a SaaS application that just automates the business process. What you have to do is deliver insights. You have to help make the people that are using these applications better at their job at some level. And the way to do that is through things like machine learning. What's interesting, Peter Burr is one of our head of research, Wikibon pointed out, last week when we were covering Mobile World Congress, he goes, it's interesting. Years ago when I was breaking into the business in the late 80s, early 90s, it was known processes, unknown technology, and those were automated. Now you have known technology and unknown processes. So getting those insights to get that discovery could really disrupt existing incumbents, big players. So someone can innovate, say, hey, I'm going to innovate on a new process that's emerging. This seems to be the big trend that's going on. And again, the software model's changing. So how do you guys see entrepreneurs looking at the AI and are they that focused on that or do they see that? I mean, what are the key areas of do they actually say, hey, I'm going to disrupt this marketplace with this one feature? We always hear the MVP or pick something, do it great. What are some of the things that you're seeing? We're really seeing two things in the AI and ML space. We're seeing one is the general kind of platform place, people that are trying to actually offer machine learning to developers in some way, shape, or form. And the reality is I think those are very difficult businesses to build. I think Google Cloud is actually extremely well positioned to be able to actually kind of drive that forward for developers based on all the work that they've done internally and the way that that cloud is built and architected. The second are applications around AI and ML and that's where we're spending the vast majority of our time because we think that that's where the most value will be created there for folks that don't own a cloud like Google. The thing that's interesting about entrepreneurs is it's been a nice thing with cloud. You can get into the game with open source and build a business. You don't have to get all that provision in the data center. That's kind of been talked about. It's not new news. Yeah, you can get up and running. But it's interesting. It was easy to get into the enterprise and then all of a sudden now as it gets more complicated, we're almost going back to the old days of it. It was really hard to crack the code in the enterprise. It seems to be a lot of new table stakes are emerging. Used to be cloud native, I'm going to go in the enterprise and you saw box.net and that became box and Dropbox, they're getting the enterprise very easily. But now as we go post, I'd say post 2012, all these new requirements start to rear their ugly head around. It's hard to get into the enterprise. So this is something that Google is certainly challenged with right now is that they have a lot of tech. They're serious about the enterprise. That's clear. But to be an enterprise contender and winner in winning deals, how hard is it to win the enterprise? And is that something that you see where the enterprise landscape has changed where it's harder or is it easier? What's your thoughts and the complexities in the enterprise? Yeah, I maybe have a different point of view than you do, which is actually, I actually think it's actually easier now to penetrate the enterprise at some level than ever has been before. But it has to start with product and open source is an incredible phenomenon that we're seeing that's kind of overtaking the way that enterprises think about building infrastructure today. I don't think you can build an infrastructure company unless you're offering it as open source software. And so what we look for in terms of investments and I think what entrepreneurs need to do is think about how do I build products that enterprises will love and then release that as open source and hope to see some level of adoption. When you see that, then that's the best path to actually them being able to go in and sell to them and building revenue around it. Kind of transitioning back to Google and what they're doing with the cloud effort. I think that their approach is actually, it's intriguing. Diane is a world class executive in this way and I think kind of brought in the last big transition that we've seen through the works she did with virtualization and I wouldn't bet against her here. I think the things that those guys are doing is offering a pretty compelling set of higher level services now that are getting traction with things like BigQuery. I think the TensorFlow is obviously very interesting and then what they've now announced recently with Spanner as a service. These are all technologies that Google understands and mastered and are very compelling technologies that I think the average developer will want and they're highly differentiated from the services that are available from the Amazons and the Microsofts of the world. Yeah, Spanner's certainly got that horizontally scalable mojo going on. They still got some work to do outside of MySQL and they're on the relational database side but we're watching. But they know that. I mean, Google's clearly not saying they're fully baked. They're actually candid in the analyst meeting. They were very candid on the security side and very candid on some of the things that they know they got to do but they are peddling as fast as they can. So I got to ask you the venture capital question developers are out there because there was a line, literally a blockbuster as they called it. People around the block had to get in. Google I.O. has had similar attraction. Those events are awesome. Google runs great events. They have, I would call them the technology store. People love to go in there and see what they have. But as an entrepreneur coming in, they're going to build on a stack whether it's Amazon or Google or somewhere else. You got to worry about the viability when you have the big gorillas out there. You got Amazon, now Google. What's the formula for this? And what do you worry about as an investor because the things you must think about is, okay, what's the approach? Where's the viability? Is there a marketplace? Is there monetization? Can they get traction? Can they go beyond the first three million in sales? Because SAS, you can get there pretty quickly as it's been discussed. What are the fears that you worry about and what advice would you give entrepreneurs as they start to start really innovating and saying, hey, I'm going to take the democratization of AI and I'm going to do some damage. I want to enter a market. These are considerations that you got to think about and you as an investor, where's the risk and what's the opportunity? Oh man, well, there are lots of risks starting a company. I mean, we could talk for an hour about the challenges associated with being an entrepreneur. It's probably the hardest job you can imagine. Having, I think that the first and foremost is you got to build products that people love and you got to solve a real problem. And so, I think for us as investors, we look for that. It's different now in enterprise investing and infrastructure and before where there used to be 10, 15, 20 million dollar efforts required to build the technology and then you take it to the enterprise and you would hope that it would sell. Now, with a couple million dollars, you have the ability to actually go out and write some compelling software, release it to the open source and see whether or not it gets traction. And then really then the challenge is figuring out whether or not you can monetize that or not. And in today's model, that's really where we struggle. It's ultimately how you ultimately package this and sell it. I think that the primary models that we're seeing are either some form of upsell on open source. So either service support, open core or an enterprise grade application built on top of the open source. The other alternative is to deliver it as a service. And we see lots of folks that are taking that open source and saying, we're going to run this as a service. We have a company in platform nine that does that for Kubernetes, but there are companies like Databricks that are doing that for Spark and the whole data pipeline. And that is potentially a very, very compelling model too. Do you have a formula for an algorithm for an investment? I remember talking to Jeremy Liu way back in the day and I just saw an interview about a Snapchat was an investor and he actually jumped into the stats with Evans Beagle and saw the traction because he was skeptical. A lot of people had passed on about that story, but is there an algorithm that you look for besides the team and being an exceptional team of people, technical shops and product shops? Is there a way that you look at the identified traction in this marketplace because it could be, there's a lot of turbulence, microservices, you've got Kubernetes and other Google innovation that's kind of becoming a glue layer, if you will, across services. Is there a way that's saying, oh that's got traction, I like that or here's some benchmarks that I look for for hurdles and ventures. Yeah, within this infrastructure space, primarily around models that are going to be delivered as open source, there's a couple of things that we can look at, we'll track GitHub stars and so we'll get a sense from that how the community views this, whether or not this is something they're particularly interested in and the level of traction they're getting within that community. It's almost like, that is almost like a stamp of approval from the technology community that says this is a really cool project, right? And then beyond that, you start to look at download volumes and to understand just how widespread the adoption of this technology is. Those are imperfect metrics, you know, and so a lot of times then it comes back to kind of switching. Market forces or whatever. Switching gears and looking at the customers and asking them the kinds of problems they're experiencing or whether or not these technologies have a chance to actually address real longstanding challenges that they've had in either building or deploying or running applications. So it's different than consumer. Yeah, consumer is a little bit easier to measure and you have a lot of data. Consumer has its own challenges and it's very difficult to kind of predict a priority what's going to be successful, but you know, it's, I think it's, the good news for us is with high quality teams, these guys typically know where to focus and where to spend time and ultimately we'll be able to create. And customer traction is always a great one to look at, I mean it's other data points. Scott, Rainey, what's new with Red Point Ventures? Give a quick plug for what you guys are doing, what you're investing in, size of the fund, how much dry powder you have as they say. Are you still writing checks? What kind of checks? We are in business and we're looking for great entrepreneurs. So we have two funds. One is a $400 million early stage fund that focuses primarily on series A and occasional series B and then we have a $400 million early growth fund that is really more on occasional series B and series C. We, you know, our attitude to the entrepreneurs is they should be indifferent as to what fund they're in, we treat every investment the same. Really, we just want to be a part of great companies and get a chance to work with them. And you guys also sponsored a party last night with the CNCF, the Cloud Native Compute Foundation. How did that go? What was some of the conversations in the hallway there or in the hallway in the event? I was at a social event, but you know, great community, the CNCF, developing a couple of new projects emerging. They've done some great work and you know, the projects that are coming in, I think all represent a lot of the foundational work that's going to be required to build cloud native applications. The first thing we did in this event last night is try to define what cloud native actually is. And I think everybody has a different definition for that. What's the most common one? Is there a trend pattern in there? Yeah, I think people were saying these are applications that are built, traditionally built using containers. They're leveraging microservices and they're built with the assumption that the underlying infrastructure is going to be ephemeral in some way. So, you know, built with that. And you have a pony in that game with HashiCorp. So, update on those guys? You know, it's a company that's doing extremely well and solving a broad set of problems around helping developers build and run applications on top of the cloud. And I think what we're seeing there and we're seeing kind of across the board is a general desire by enterprises to start to think about multi-cloud, to start to understand what it takes to actually deploy applications and run applications across multiple clouds and also to be more agnostic about what the underlying substrate looks like. And you know, those are trends that have been bowed well for Google and Microsoft. Yeah, we're excited. Scott, thanks for coming on. We're going to be watching that Kubernetes, that orchestration layer that's going on around microservices. It's a hot, I'd say, battleground around innovation. A lot of good things happening there. Great opportunities when there's a lot of turbulence. There's great opportunities to invest. Good luck with your investments. Scott Rainey, partner at Red Point Ventures. Very active in the community. Great VC, check them out. This is theCUBE, two days of live coverage all day. Going to 4.35 today and then tomorrow, Thursday. And then we're off to South by Southwest again. More coverage, we'll be back with more coverage after the short break.