Live from Las Vegas, it's the Cube. Covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. And welcome to Las Vegas! We're at AWS re:Invent, day one of three days of coverage here on the Cube. Along with Justin Warren, I'm John Walls. Glad to have you with us here for our live coverage. We're joined now by Jonsi Stefansson, who's the vice-president of Cloud Services at NetApp and Hákon Guöbjartsson, who's the CIO of WuxiNextcode. Gentlemen, thanks for joining us, good to have you here. >> Thank you. >> Yeah, thank you for having, >> Having us. >> And I think, not only your first time on the Cube, but I believe the first time we have had natives of Iceland, I believe. (laughs) >> So, a first for us as well. But glad to have you. First off, Háken if you will, tell us a little bit about WuxiNextcode, what you do and why you're here. >> Yeah, so we are a company that specializes in analysis of genomic data, all the way from gathering cohorts for our pharma customers into providing sequencing services, data analytics, and AI. So we basically cover the full end to end solution space for genomic analysis. >> Okay, and now let's talk about the partnership, or at least the work that's going on between you, if you would, Jonsi, a little bit about when you have a client like this, genomics, what exactly are you trying to peel back for them? What's the challenge that you're trying to address for them? >> So we started Cloud Volumes Services on AWS roughly eight, uh, six months ago. And we've been running it with very selected customer base that is focusing on very specific workloads, like genome sequencing, rendering, database workloads, like workloads that have traditionally have had a hard time finding themselves into the cloud. So we've had a very deep partnership with WuxiNextcode in sort of customizing our offering that fits their needs. So we've been working very closely with them for the past I would say four to five months, and now we've moved their entire production sets into AWS. So that's been something that these research companies have been struggling with. And the Cloud Volumes addresses that, with the data management capabilities and the performance tiers that we offer. >> Could you give us a bit more detail on what it is about Cloud Volumes that's special and different compared to what you would generically get from AWS. Because people have been able to put storage into the cloud >> for some time, >> Of course. >> so what is it about Cloud Volumes that's unique? >> So I think we're very complementary to the storage offerings that AWS has currently. Like WuxiNextcode is running for traditional database, they are using 53 instances, EC2 instances, that all have EPS volumes. But for the analytic data, it actually gets pushed to NFS. So we are basically just have a more performance solution for shared everything solution. If you compare that to EFS for example, EFS is a great offering that AWS already has, but it doesn't reach into that scale, for example, when it comes to the performance tiers that we are offering. We also offer a differentiator for the customers to be able to clone and snapshot data, and only the tester, not to a full copy. So for example, it's really important for data scientists like WuxiNextcode to always be working on production datasets, for like data scientists. So for them to be able to replicate the data across all different environments, testing, staging, development, and production, they basically only have a small tester difference in all those volumes. Which is really important, instead of always having to copy 40 terabyte chunks, they're basically just taking the different between all of them and using the on tap cloning technology. So that's a very unique value proposition. Another unique value proposition of Cloud Volumes is you can automatically or dynamically change the performance tiers of the volume. So you can go from standard, premium, to extreme dynamically, based on when you actually need that extra level of performance. So you don't need to be continuously running at extreme, but only when you actually need to. >> So Háken, what was it about the Cloud Volumes that got your attention initially, that said "actually, this is something "that we should probably look at." >> I mean, so a little bit of a background, we kind of grew out of an environment where we were sort of evolving our architecture around an HPC cluster architecture with highly scalable storage, and actually we were using NextApp storage in our early days when we were developing. Then as we moved into the clouds, we were somewhat struggling with the NFS scalabilities that were available in the cloud. So I sort of like to say that we are kind of reborn now in the clouds, because we have lots of interactive analytics that are user-driven, so high-speed IO is fundamental in our analysis. And we were in a way struggling to self-manage NFS storage in the clouds. And now, Cloud Volumes was in a way, sort of like a dream come true. It's a lot of simplification for us in terms of deployment and management, to have a scalable service providing the NFS sort of service to our applications. So it was a perfect marriage in that regard. It fitted very well with our architecture, even though we use some of our storage relies on optive storage, but all the interactive analytics are performing way better using NFS storage. >> Yeah, Hákon, were there reservation making this move? I mean when, or capabilities that you thought maybe it sounds good, but I don't know if you can deliver on that and things on which you've been pleasently surprised? >> To a certain extent, because we had actually tried several experiments with other solutions, trying to solve sort of the NFS bottleneck for us, and so when we tried this it actually went extremely smoothly. We onboarded 50 terabytes of data over less than a weekend. And when we ran our first sort of test cases to see whether this was working as expected, we actually found it worked over three times better than with our conventional storage. And not only that, there were certain use cases that we had never completed really to the full end, and we were finishing them in times that we were very pleased with, so. >> I mean they were actually running, I mean our goal for the workshop that we did, and we've been doing this with a lot of customers, one of the sort of challenges Hákon came up with was query, a genome query that he created that he was never able to complete. And he wanted to see if by switching this out, he could actually complete that query. And it used to time out in like three or four hours in his time down. >> It was essentially a query that was touching on something on the the order of 20 trillion data points, so we were using lots of quartz. We have a database solution that we have developed which is sort of a proprietary database for genomic analytics, and it was spending up over 500 quartz essentially. And so it was a very kind of a IO intensive query. But as I said, we were able to run that to completion actually in a time that we were very satisfied with, so. >> That's pretty amazing. >> Yeah. >> Absolutely. >> So Hákon, what's your impression of NetApp's data fabric vision? They've been talking about that for a little while, and I'm just curious to hear what your take on it is. >> Yeah, I think it makes a lot of sense. I mean, we work with many pharma customers that have lots of data locally, but are also looking at the cloud as a solution for growth and for new endeavors. And having a data fabric infrastructure that allows you to bridge the two I think is something makes a lot of sense with where people want to go in the future. >> Yeah, what are you hoping to hear from Amazon and the show around that idea of being able to live outside of the cloud? Traditionally, Amazon's been very keen on saying, "no, no, everything must be here and in the cloud." They're not so keen on this idea of a data fabric that could move things around in different locations. What are you expecting to hear from them this week? >> I mean, I wouldn't say so much that I'm expecting to hear something, but it's clear for me that customers are more willing now to go into the cloud, but regardless of that, there's still certain reasons to keep certain infrastructures still where it is, moving legacy infrastructure into the cloud may not be necessarily the best way forward, rather to be able to integrate it more seamlessly with the cloud and evolve the new functionality, new features in the cloud. And also there are some, I wouldn't call it privacy, but there are lots of data sets that people are reluctant to move into the cloud still because of the way they are managed, et cetera. And being able to bridge those two things is something that I think is valuable for our customers. >> I actually don't think that the decision to move into the cloud, it's never been a cost decision, in my opinion. It is for companies to actually be able to compete with other companies within their sector and to take advantage of the rapid innovation that is happening in the cloud. I mean, if you take autonomous vehicles for example, the companies that are actually in the cloud and taking advantage of like Changemaker and like this deep learning and machine learning algorithms, it's really hard to compete with AWS, it's really hard to compete with Google or Azure. These are really big companies that are pouring a lot of money into innovation. So I think it's always, it's driven by necessity to stay competitive, to go into the cloud, and being able to tap into that innovation. This actually brings into the sort of, what does it mean to be cloud native? If you're cloud native, it means that your solution, even though it's being serviced through a marketplace, it needs to be able to tap into that innovation. You need to connect to that ecosystem that AWS has. To me, that's a much stronger driving force to drive those legacy applications into the cloud. But with the data fabric, we want to really bridge the gap. So it should be relatively easy for your application or your workload to find the best hope at any given time. Whether that's on premise of in the public cloud, you should have like a, an intelligent way of deciding where each one of your workloads should go. And that's the whole point of the data fabric. Make that really, really easy. >> Well you said the partnership's been about four months, so you're still in the honeymoon, but here's to continued success and thanks for being with us here on the Cube. We appreciate it. >> Thank you so much for having us. >> We are happy to be here. >> Have a great show. Back with more, we are live here on the Cube at AWS re:Invent and we'll be back with more in just a moment. (energetic music)