 You are CUBE alumni from Silicon Valley. It's theCUBE covering Google Cloud Next 17. Welcome back to theCUBE's coverage of Google Next 2017. I have a lot of conversations is how enterprises are really grappling with cloud, move from on-premises to public cloud, multi-cloud, hybrid cloud, all those pieces in between. Happy to welcome the program, a first-time guest, Paul Scott Murphy, who's the Vice President of Product Management at WAN Disco. Thanks so much for joining us. Yeah, thanks very much. It's great to be here and join you on the program. All right, so, Paul, I think a lot of our audience probably is familiar with WAN Disco. We've had many of your executives on, really dug into your environments for the last few years, usually see you guys at a lot of, not only the big data shows, we've got Stratocomin up next week. Last time I did an interview with you guys was at AWS Reinvent. So, WAN, replication data, all those things put together, you've got a big bucket of big data in cloud. Tell us a little bit about kind of your background, your role at the company. Okay, so I've been at WAN Disco now for about two and a half years. I've previously worked for Tipco software for a decade, working out of Asia Pacific, held the CTO role there for APJ, and joined WAN Disco two and a half years ago, just as we were entering into the big data market with our replication capabilities. I now run product management for the company and work out of our headquarters here in the Bay Area. Great, and connect with us, you know, what you guys are doing at Google, what's the conversations you're having with customers that are attending. Yeah, so Google is definitely one of the key strategic partners for WAN Disco, obviously particularly in the cloud space for us. We're hosting a booth there for the conference and using that as an opportunity to speak to other vendors and the customers that we have attending the Google conference, particularly around what we're doing for replication between on-premises and cloud environments and how we support Google Cloud Dataproc and Google Cloud Storage as well. Yeah, can you help unpack for us a little bit? You know, where are your customers? Give us, you know, typical customers that, you know, they're saying, hey, you know, I want to start using this cloud stuff. You know, how are they, you know, figuring out what applications stay on-premises, what goes to the public cloud, and that data piece is, you know, a challenging thing. You know, moving data is not easy. There's a whole data gravity piece that fits into it. Maybe you can help walk us through some of the scenarios. Yeah, as we're progressing the technology, we're certainly finding a broader and broader range of customers getting interested in what they can do around data replication. The sorts of organizations that we deal with primarily are those who are looking to leverage both on-premises and cloud infrastructure. All those who are moving from a situation where they've been toying with these environments and moving into production-ready scenarios where the demands of enterprise-level SLAs or availability or the needs around disaster recovery, backup and migration use cases become a lot more dominant for them. The organizations that we work with, typically the larger organizations, we deal a lot with retail, with financial services, telecommunications, with research institutions as well, all of whom have larger needs around taking advantage of cloud infrastructure. Of course, they all share the same challenge of the availability of their data, where it's sourced from, isn't always necessarily in the cloud, taking advantage of cloud infrastructure then, requires them to think about how they make their information available both to their on-premises systems and to the cloud environment where they can run perhaps larger analytic workloads against it or use the cloud services that they would otherwise not have access to. Yeah, one of the challenges we've seen is when we've got kind of that hybrid or multi-cloud environment, managing my data, kind of the whole orchestrating pieces and getting my arms around how I take care of it and leverage it, can be challenging. Is that something you guys help with or are there other partners that get involved? How are customers helping to sort out and mature these environments? You know, it's a big question, of course. You've touched on the management of data as a whole and what that means and how organizations handle that. When this goes wrong, in supporting organizations with those challenges, is an ensuring that when they need to take advantage of more than one environment or when they need their data to be available in more than one place. They can do that seamlessly and easily. What we purport to do and what we encourage our customers to do with our technology is rather than keeping one copy of data on-premises and using it solely there or copying your data to another location in order that you can act upon it there, we treat those environments as the same and say, well, have the best of both worlds. Have your data available in each location. Let your applications use it at local speed and do that without regard to the need for retaining a workflow by which you exchange data between environments. When this goes, technology can take care of all of that and to do so, it has to do some very smart things under the covers around consistency and making that work across wide area networks. Makes it particularly suited to cloud environments where we can leverage those underlying capabilities in conjunction with the scale of the cloud, which is a native home for data at scale. Can you give us some, where do you see customers kind of in this maturation? Dangreen made a statement that today, 5% of the data is in the public cloud. So what are some of those barriers that are stopping people from getting more data in the cloud? Is it something that we will just see a massive adoption of data in the cloud or what's your guys viewpoint as to where data's gonna live, how that movement is happening? I think longer term, the economic advantages of using cloud environments are undeniable. The cost advantages of hosting information in the cloud and the benefits that come from the scalability of those environments is certainly far surpassing the capabilities that organizations can invest in themselves for their own data centers. So that natural migration of data to the cloud is a common theme that we see across all sorts of organizations. But as many people say, data has gravity. And if the majority of your application information resides today in your own environments or in environments outside of the cloud, whether that's internet connected devices or points of ingest that reside outside of cloud environments, there's a natural tendency for data to remain in place where they're either ingested or created. What you need to do to better take advantage of cloud environments then is the ability to easily access that data from cloud infrastructure. So the sorts of organizations that are looking to that are those with either burgeoning problems around consuming data at multiple points. They might operate environments that span multiple contents. They might have jurisdiction or restrictions around where their data can reside but need to control its flow between separate environments as well. So when disco can certainly help with all of those problems, underlying replication technology that we bring to bear is very well suited to it. But we are a part of the overall solution, right? We're not the full answer to everything. We certainly deal very well with replication and we believe we cover that very well. Yeah, I'm curious to talk about kind of the dispersion of data and where it's being created. Of course, edge use cases for things like IoT are quite a hot topic at that point. Is that something you guys are touching on yet? Gets involved in discussions. Where does that sit? Yeah, definitely. The interesting thing about WAN disco's approach to data replication is that we base it on this foundation of consistency and using a mathematically-approven approach to distributed consensus to guarantee that changes made in one environment are represented in others equally regardless of where those changes occur. Now, when you apply that to batch-based data storage or streaming environments or other forms of ingest is relatively irrelevant so long as you have that same underlying capability to guarantee consistency regardless of where changes occur. If you're talking about IoT environments where you naturally have infrastructure sitting outside of the cloud and this is the type of infrastructure that needs to reside out of the cloud, right? Your edge points where data are captured, where you're consuming information or generating it from devices, perhaps from an automotive vehicle or from an embedded device, some sort of sensor array, whatever that happens to be. These are the types of environments where it means you're generating data outside of the cloud. So if you're looking to use that inside of the cloud itself, you need some way of moving data around and you need to do that with some degree of consistency between those environments to make sure you're not just challenged with extra copies of information. The other really interesting topic around data that's being discussed at the Google Cloud event is artificial intelligence, machine learning. I'm curious, are your customers involved in that? Where do you see that kind of on the radar today? Yeah, it's obviously an absolutely critical part of where the IT industry in general is going and the type of solution that's fed off data, right? These systems are better as your data set grows. The more information you have, the better they work and the more capable they become. And it's certainly an aspect of how well machine learning techniques and artificial intelligence approaches have been adopted in the industry and the rapid rate of change in that side of IT is driving a lot of the demand for increasing access to data sets. We see some of our customers using that for really interesting things. You might have seen some of the recent news around our involvement in a research project led through the University of Sheffield looking to use data sets captured from a variety of research institutions and medical environments to solve the problem of identifying and responding to dementia. And it's a great outcome from that type of environment through which machine learning techniques are being applied across data sets. What you find, though, is that because there's a large set of institutions sharing access to data, no single data set is sufficient to support those outcomes, regardless of what intelligence you can place against the machine learning models that you build up. So by enabling the ability to bring those data sets together, have them available in a single location, being the cloud, where larger models can be assessed against the data sets means much better outcomes for those types of environments. Okay, Paul, in your role of product management, we went through some of the hot buzz terms out there. How do you help the company identify those trends focused on the ones that are important to your customers and the kind of feedback loops that you get from them? Yeah, I guess a lot of work in the end is how we do it. But we need to listen to customers directly, of course, understand what they are looking to do with their information systems, what they're aiming for, their goals at a business level, what type of value that they want to get out of their data and how they're approaching that. That's really critical. We also need to look to the industry in general. We're obviously in a very rapidly changing environment where technologies, the organizations that build IT systems are increasingly adopting new approaches and building systems that simply weren't available days ago. Look at the announcements from Google of late around their video intelligence APIs as a service, their image APIs as well, all new capabilities that organizations today now have access to. So bringing those things together, understanding where the general IT trends are, how that applies to our customers and what WAN disco can do with the unique value that we bring is really key to the product management role. All right, Paul, you've been at the show. Curious, any cool things you saw, interesting customer conversations that may want to give our audience a flavor of what's going on and why 10,000 people are excited to be at the event? Yeah, well, it is a very exciting event. Just the scale of these types of events run by Google and similar organizations is something in itself to behold. We're really excited to be a part of that. The things that are really interesting for me out of the show tend to be where we see customers or opportunities coming to us, identifying challenges that they can't address without the type of technology that we bring to bear. Those tend to be areas where either they're looking to do migration from on-premises systems into the cloud, which is obviously very strong interest for Google themselves. They need to bring customers in to take better advantage of the services that they have. WANDISCO can play a strong role in that. We're seeing a lot of interesting things around the edge too. So all of the ways in which data can be used are always exciting and interesting to see. The combination of technologies like artificial intelligence, like virtual reality, the type of work that WANDISCO does also is certainly going to bring forward, I think, a new wave of applications and systems that we just hadn't considered even a few years ago. Yeah, lots of really interesting things. There's personal assistants at home and personal assistants that are listening okay Google, subscribe to SiliconANGLE on YouTube. We'll be back with lots more coverage here from theCUBE talking about Google Next 2017. You're watching theCUBE.