 From Silicon Valley, it's theCUBE, covering Google Cloud Next 17. Okay, welcome back everyone. We are here live in Palo Alto for two days of coverage of Google Next 2017, special coverage brought to you by Intel, I want to thank Intel for sponsoring our editorial coverage of Google Next. Obviously Cloud Service provides a huge opportunity. Cloud is changing the digital transformation and I want to thank Intel for that. Breaking down the coverage, going into the realities of Cloud, our next guest is Pedro Abrari, who's with Pramada, Chief Technology Officer. You guys do a customer digitization of Cloud Platform based in Silicon Valley, you're a veteran former entrepreneur. Welcome to theCUBE coverage of Google Next. Thank you, John. So first tell us about what you guys do as a company. And I know you guys have an interesting story because you're in the heart of the Cloud game relative to operationalizing it. And it's complicated in being an enterprise Cloud solution. There's nuances there. There's some tripwires, there's some landmines, whatever you want to call it. What do you guys do? Let's do a quick background. So what Pramada does is we are a B2B platform for large enterprises such as NCR, HP, CenturyLink, who have hundreds of, in some cases, thousands of customer contracts and don't have a handle under contracts. We digitize those contracts and those customer relationships and we layer intelligence on top to allow key decision makers in those businesses to have a single unified and up-to-date view of the state of each customer relationship at any point in time, layering on top billing data and CRM data and MTM data. And what's interesting, what I like that you're here is that it really hits the theme of Google Next, which is data, data sets, machine learning, AI, pointing to a new model of how software's changing applications. So you guys are at the middle of this digital transformation. And it's a whole new paradigm. It's not like the classic linear thinking of supply chain or CRM kind of thinking. You guys are truly data-driven and this teases out the complexities. So what's your thoughts? Because again, Google is clearly going down to the enterprise level, as is Amazon, a little bit ahead of them in terms of progress. But this is the trick everyone is doing in the digital transformation. I want to leverage my data. I want to move to a cost-effective infrastructure or it could be a startup saying, hey, I want to get into the game and I want to innovate on a feature and then there they are. They could be the next Snapchat out there watching. This is important, but it's also hard. What's your thoughts on the landscape of this opportunity? Well, cloud computing definitely changed the game for high-tech startups in a big way. When infrastructure as a service first rolled out with AWS as kind of the tip of the spear, the virtualization of hardware was a big game changer because as a startup to even get in the game, you had to have millions of dollars worth of investment in just hardware and software. And every two or three years, you had to renew all your hardware and software because they're out of date. So before you could even focus on your core competency, there was all these layers of investment and all the talent that you had to attract just to deal with getting a cloud software up and running. With cloud computing, particularly with infrastructure as a service, it changed that game, virtualized hardware and it allowed a lot more companies to have access and the ability to get into the game that couldn't previously. But the story doesn't end there. It's just the beginning of the story because to get a cloud software really up and running, you still have to have a team. Traditionally used to be IT teams, but it's kind of the evolution has come. Now we have DevOps teams for good reason who have to build a lot of additional plumbing on top of the infrastructure as a service until your cloud can be up and running in a scalable, cost-effective, plastic fashion, if you will. Yeah. Tell about the scale piece because this is interesting because you have a lot of experience in scaling with the cloud. This is the main thing that people are leveraging with the cloud is that I can scale up pretty quickly, scale up and scale out. And then the complexity is the digitization piece which is more specific to the enterprise. What are some of the challenges that you see with scale? Because this is something that needs to be factored in on the design side. So digitize, oh yeah, I want to digitize my entire company. Okay, sounds easy. But the scale piece is important because you now have scalable stuff. Right. How does it all work? Cloud software, early on in the cloud days, we had IT teams and we had developers who were really enterprise developers. And they looked at the world with those glasses on. And very shortly thereafter, as soon as the first cloud software was up and running, people realized, wait a minute, the old way of building software just doesn't work anymore. You have to rethink, this is where DevOps developed, where it was a culture of developers and operations all working in concert, always designing software for scale in the cloud. It's a very different paradigm. And things such as transition from stateful services to stateless services to microservices, it all continued to turn services into things that could run and spun up and run across a large cluster of servers as opposed to something that only scales vertically on a single box. But if you think you have a service that you can throw on the cloud and you can magically get the benefits of that and costs get lowered, I'm here to tell you that if you don't play your cards right, it blows up in your face very quickly. Give an example, because this is the trade off, back to the trade off conversation, right? Yeah, yeah, an example is if you have software that doesn't scale horizontally, that is not elastic, it doesn't scale and it only scales vertically and you throw it in the cloud and the more load gets on that software and that service, the only way to go is to keep getting bigger and bigger boxes that are available on AWS or on Google or on Azure. And the larger the box, the more expensive it becomes. The whole premise of cloud computing was commodity boxes and things that could scale this way and you really are basically going back to the same old problem you had on the enterprise side, having to get bigger and bigger and bigger boxes. That can really blow up in your face in terms of the cost that people would be shocked, the kinds of bills that they can receive from some of the cloud vendors if they don't manage and contain their problem effectively. We have Pedro Marbrari who's with the CTO of Primata. They bring up an interesting point, I want to jump in and just kind of double down on that because the classic IT enterprise conversation in the heyday of enterprises that was developing was the shark fin, the tip of the iceberg. What you don't see under the water is the hidden costs, right? Oh, massive. The total cost of ownership has always been a big issue. And if you look at things like OpenStack, for instance, great on paper, great philosophy, but the total cost of ownership has really kind of crippled that from being, other than anything more than infrastructure as a service. So there's trade-offs for an enterprise when they look at the total cost of ownership saying, I'm just gonna throw everything in the cloud and run multi-cloud and everything's gonna be managed perfectly and there's manageability and there's security, I'm all set. No. No, or is it that? No, no. I mean, why is that so important? Because there's some trade-offs specifically here. There is, so first of all, multi-cloud. Cloud neutrality, in theory, it sounds great, but it comes at a very expensive price. If I'm running on Google or if I'm running on AWS and if I commit to running only on AWS, run Google or Azure, for that matter, I have the opportunity to leverage some of the managed services that are offered up by the vendor and they have the world's foremost experts at running some of these services. Let's say your software requires a relational database. If you're gonna be cloud neutral, you have to host that database, deal with backup recovery, scalability, failovers, all of that overhead associated with it, which means you have to hire world's foremost experts at doing these things and you have to attract them, you have to pay them and on top of everything else that's associated with having to anticipate the heaviest load of your system and always planning for that, if you can leverage the Google Cloud SQL or if you can leverage AWS RDS. But Google does not only run my SQL, they don't run anything else. That's true, that's true, but AWS does. They have a plethora of different databases. So it's good to go to AWS in that case. Well, if you're starting from ground up and you're a startup, committing to my SQL is just fine. If you already have- Which is why Google is really doing well on the cloud native piece. Exactly, exactly. And enterprises who have other databases and other relational databases. Yeah, and so if you already are sitting on top of a legacy that you have to support, then going to AWS might be easier. But AWS has its own complexities because it is a massive service. It has a lot of APIs, it has a lot of complexity, so you have to deal with all of that complexity. Even the billing side of AWS has a whole economy all to itself. There's all these vendors that exist just for managing AWS costs. So having a model like Google which is just a lot more simplified and kind of reduces the explosion of complexity that you potentially deal with on the AWS side may work just well for a lot of startups. This is really an important point I think because it's something that's not being covered much in the press or in the analyst community is that everyone certainly talks about locking. Oh, the Roche Motel you can check in but you can't check out. And I've heard that been called to Amazon and everyone else, the lock in. But if you look at what you're saying is interesting. You say lock in actually in contrast to say the opportunity you're leveraging say manageability and security is not a big deal given the fact that you don't want to have to build those services. If you go to fully neutral cloud where I'm going to have multiple workloads then it's on me or an IT to build the software fabric for manageability. That's exactly right. So the risk is if it's not available if there's no software that does that, that's the risk. That's what you're getting at. As a serial entrepreneur has done who has done numerous startups, one of the key aspects of doing a startup is focusing on your core IP and your core differentiation. Your core IP is not how to run a cloud software. It's other people's IP and you should leverage that. Platform as a service is a way to leverage that and you give up some control you fall into a platform as a service. And for that matter, if you want to fall into a platform as a service you can fall into a platform as a service on AWS or you can do it with the Google App Engine or you can do it on Azure but you can basically see which one fits your needs and your profile and your software best and just give up control for productivity and for cost reductions and also you get gain from all the expertise and best practices they have developed around security and audit and all the ramifications around basically making sure that you take care of your customer data safely and securely and you don't expose them to risk. And this is interesting because it makes the cloud argument more about the beauties in the eye to behold or whatever the enterprise thinks is best. With cloud media that might be Google but then it's an opportunity for the vendors to differentiate on certain services. So I get that, but the question I want to ask you is for the folks watching who are in the enterprise trying to squint through all the complexities. Hey, I'm on a digital transformation. I don't know what's what. I'm seeing Google say this, Amazon says this, it's apples to oranges. You know, what's in it for me? I have my own enterprise. So that's an interesting conversation. So the question is what would you advise enterprises to evaluate when to go with Google? When to go with AWS? When to go with Oracle or IBM? There's a variety of different choices. When do you evaluate that trade-off factor of what to leverage? How do you advise that? It's a tough nut to crack. You know, before you even move to the cloud you can still do some soul searching internally and look good, bad, or ugly of your own software. You know, what are strengths? What are scalability issues? You know, can it scale horizontally? Can it only scale vertically? And with that in mind, then you go and evaluate the options that are available out there. You know, if you are never going to leverage any of the native cloud services that are offered up by AWS or Google or Azure, and you only want to, let's say, you want to be completely dockerized and containerized, and you really want to kind of follow that model, maybe these services don't matter to you. And you're willing to take on all that responsibility and manage all those services. So you really have to, and I would strongly advise that you gain, you know, and go to cloud experts who have done it before, time it again, and seek their insights and advice, and not jump into the pool thinking that, oh, it's just cloud, I mean, anybody can do it. Question for you on, say, Google for instance, say that you and I were called into the Diane Green's office and they said, hey, Pedro and John, I want you to advise me. We really have good dev developer empathy. We talked about this in our last segment, developer empathy, but we don't have a lot of empathy for enterprises. You guys are expert in the enterprise. What should we do to empathize with the enterprise better? What would we advise them? What would we go in and say to her and her team? I would say start with the pain points of the enterprise, right, you know, before the enterprise was even considered moving to the cloud, their biggest and primary concern is security. You know, they have to make sure that they can trust you. And of course that has really over the years has been chipped away at the old obstacles are falling one at a time, but really being able to speak their language and get them to be comfortable that they're in a following best practices in a very solid and secure environment. And on top of that, you know, help them with all their audit needs. You know, everybody wants to get certified. And a lot of that, when you actually move to the cloud, if you have a Google or AWS on a checkbox, a lot of those questions that others asked go right out the window. So that is a helpful factor, but helping them along those lines and also cost factor. A lot of people don't know what it's gonna cost. And you know, cost calculators and all that stuff are good and great, but they only go so far because there's a lot of hidden costs that you don't associate with it. A lot of it can come in the form of talent and expertise. A lot of it comes in the form of just, you know, paying for services. The SLA too, I mean, SLA is a huge one. I would say to Diane, look at, you know, being a price leader, and you certainly could have great pricing, but I don't think the enterprise is price sensitive. I think they're SLA sensitive. They are, right. And that's kind of their weak spot a little bit here. It is, and of course, you know, now Google has a little bit of an advantage to kind of something to kind of bring to the table with what happened to AWS last week. But again, if you take the big picture of the SLAs that are offered up by any of these cloud platforms, compared to what you could do internally, hosting your own services with your own IT team, I'll bet you they'll beat your IT team every day of the week twice on Sunday in terms of SLA. So I wouldn't be afraid of moving to the cloud. And you know, and again, things, hiccups happen to anybody and everybody. Well, I mean, you know, Pedron, one of the things we saw clearly this year at AWS, we've done all the live broadcasts for years. And but this year what was clear is that the speed of what Amazon has been innovating services and Google needs to match this cadence as well on their side for their architecture is one of those cases where they're doing it faster than the IT guys could do it. So it's the same argument that open source is a great value because open source is moving the needle faster than homegrown teams could do on IT. So that's an opportunity to leverage that to focus on the core competency of the energy. Absolutely. And then one of the other things that people overlook when you leverage an AWS RDS service, what you gain is not just what they have at the time, what you also gain is all the improvements that happen over time on their behalf, on their side, where they keep increasing their throughput and performance and scalability. You know, AWS just came out, you know, really with the not just but the Aurora service, which is effectively like a, acts like an elastic relational database, which is a concept unheard of, you know, and imagine trying to replicate that internally. I mean, it is things that, you know, the level of expertise they bring to bear and the level of resources that they bring to bear to really solve these complex problems far outweigh anything that we would have in, you know, in our company to be able to address those various challenges. Pejron, great to break down some of these trade-offs. This is the nuances of the enterprise being empathetic is to really understand the buy-bill kind of concept versus when do you want to leverage your core competency, when do you want to shift that capability to a cloud or a certain cloud, certainly the criteria. Really appreciate you taking the time. Take us a little, take a minute to talk about your company. What are you guys doing? Because you guys are in the middle of digitization. We have to do transformation and it's not that easy. No. What are you guys doing for customers and what's your competitive advantage? So what we do is, you know, we have a lot of large enterprise customers who typically have hundreds of thousands of customer contracts that nobody ever looks at or reads or, you know, or you're only reading an army of lawyers who really comprehend and understand and this is an obstacle to making good business decisions to grow your company. So large enterprises, much like small enterprises, need a up-to-date view of their customer relationships which starts with a customer contract which is where we come in and we digitize the customer contract and we extract key information out of it, the information, not all the legalese and noise, but really the core data, the core key decision-making data that you need to have to interface with the customer. We extract that out and make it available to you in an environment that is accessible by anybody, not just lawyers. On top of that, we bring in data from across your enterprise about that customer, you know, whether it's your billing systems or CRM systems or MDM systems, you name it, we can bring all of that data layered on top of your contract data and on top of that, introduce additional layers of intelligence where it tells you what is the most up-to-date aspect of your customer relationship information and that allows you to make, you know, real-time important decisions that, you know, over time, your finance teams and sales ops teams can really match the customer relationship. This is classic data-driven where you're taking core data about the customer and contract, they pay for stuff, they have some key data in their system of record, if you will, and kind of sharing it into other systems Sounds like it's perfectly poised for machine learning and AI. Is that what you're talking about? That is our secret to us, you know, trying to ingest and digitize hundreds of thousands of contracts cannot just be done manually, clearly. It's not just a sales thing, it's more of the operational impact. Renewals is a big issue. There's massive operational impact. There's upsell impact. There's a lot of, you know, our customers gain after, you know, adopting us, you know, millions of dollars in lost revenue potential where they are thrilled to tell us about it. Like, we have found all this money we didn't know we had. It's kind of like having untapped knowledge base and data in big data. Yeah, everybody knows there's information there that we could use, but to tap it, you go to machine learning. Cross-pollinating core data and making it addressable for other apps. Precisely right. Okay, Pedro, thanks so much for coming and sharing your perspective. Breaking down the two days of special coverage of Google Next, this is theCUBE, live in Palo Alto, we've got folks on the ground, our reporters, our analysts, they'll be calling in, and of course we've got an exclusive scoop with SAP, we have one of their top executives who runs the Palo Alto entire facility, all the folks came in from junior. We had a chance to sit down with SAP, that's coming up shortly. Stay tuned for more coverage live in Palo Alto. For Google Next 2017 in our studio, we'll be right back with more after the short break.