(upbeat music) >> Hello everyone, and welcome to this Cube conversation. We're going to dig into some of the more specific and sometimes gory details of managing the nuances of database, database management systems. You know, it's a lot of fun to get it to the daily buzz of cloud and database competition and get a little snarky on Twitter, but there are a lot of mundane issues that you have to address to really do proper database sizing, capacity planning, and you know whether or not database consolidation makes sense. These are not trivial issues. And decades ago they spawned an entire role around the database administrator. They had to do the dirty work of database management so that users and customers would be satisfied. And while automation and cloud are changing that role, at the end of the day, somebody actually has to make the databases work in the cloud and make sure that the business doesn't feel any impact on the transition along the way. So on that note, we have with us Oracle senior director of product management for mission critical databases. He works in Juan Loaiza's group, Chris Craft, and Steve Zivanic whom we know well on the cube says this guy is the Jedi master when it comes to consolidating databases in the cloud. Nobody knows more on the face of the planet Earth. So we're really excited Chris, to have you inside the Cube. Welcome. >> Thanks, thanks Dave. >> That's a very humble thanks. So when it comes to running databases in the cloud can you explain the difference between sizing and capacity planning? Aren't they two sides of the same coin? >> Yeah, you know, they really are. It's like, you know sizing is really part of capacity to planning. It's really, I look at sizing as a one-time effort whereas capacity planning is more your ongoing. You perform sizing initially when the application is deployed. And then, then when you're changing platforms, like going from on-prem to the Cloud you're going to go through a sizing exercise 'cause you're looking at going to a new platform. That's more of a one-time effort, and then ongoing, you're looking at your capacity management over time. So yeah, they are very related so. >> Okay, thank you. So we're going to talk about database consolidation. A lot of people would say, look the cloud makes consolidating databases maybe not irrelevant, but maybe not the best strategy because I got all these different purpose-built databases. Why consolidate databases if they're already going to consolidate it in the cloud in one location? >> Yeah. So, so we're really talking about in in the cloud, you're running virtual machines but consolidation still applies on the virtual machines. So if you have a virtual machine that's dedicated to a database that database is that server, that virtual machine is going to be under utilized over time. So what we're doing with consolidation is running multiple databases within a virtual machine or what it, Oracle virtual cluster. We do everything on clusters. So multiple machines multiple databases within that will drive up the utilization and improve your cost structure. So it's a sizing it's it's absolutely critical on even in the cloud. >> Okay. But, but wouldn't it, I might say to that, wouldn't it be better to have each database have a dedicated VM? I mean, from a performance perspective, it doesn't try to make the database do too much affect performance. >> Yeah. It, so whenever, so we know historically that a database on a dedicated server back in the day that was a physical server, today it's a virtual machine. When you do that, your utilization will be in the range of 15 to 20%. And that's, you know very highly under utilized systems when you do that. So we don't need to isolate things onto dedicated virtual machines for a performance perspective. There are other ways that we can manage that we have resource management built into Oracle and the Oracle database. And then on Exadata we have an integrated IO resource management as well so we can deal with that different ways. >> Okay. So you're basically proposing that you're putting these databases onto a single VM and managing it accordingly. Is there additional details you can provide on that? >> So, you know, we don't put everything into you know, literally one, one VM. You want to have some isolation built in there, but see and take a more pragmatic approach. You know, like every single database in one VM that's the wrong way to go. Each database in a dedicated VM is also the other extreme, also the wrong way to go. So we're kind of right down the middle and be more pragmatic about it, and do some level of consolidation to drive up utilization. >> I remember when I first started following tech I was studying up on, you know kind of how disc drives work and so forth. And there was probably like I can't even remember what it was. It was like probably like 10 megabytes under an actuator. And people were saying, Oh my God, that's so much data. You, you got your blast radius is, is so big. You got to split that up. So it's the same concept, apply with availability. Some would say, there's a problem because you're consolidating all this data and you've got this blast radius that increases. How do you address that? >> And so, you know, redundancy. So we have redundancy at all levels. So if you look at a single, so we're talking about Exadata here, taught in an Exadata machine we can lose up to 24 disc drives out of 30. 30 machines with 36 disc drives, we can use 24 of those. So that'd be 12 per storage cell. You can lose two storage cells as 24 out of 36 drives so we can lose and keep on running. We can also, we also cluster, we also do clustering. So the database servers are clustered together for high availability. So we can take, we can suffer multiple simultaneous failures and keep on running without performance impact either. So it's, so recovery, we handle that in different ways. So it's, look at blast radius from a standpoint, you want some, some isolation for blast radius but we have physical failures is just not something that we're concerned with. >> Why do you deal with taking down a VM? Doesn't that normally mean there's going to be some kind of disruption? >> Oh, so you know, the, so Oracle database, you're talking about real application clusters on on Oracle database, on Exadata. We've got, we have a very fast detection of of failures and then resolution of the failure. So we're looking at a small blip in performance, you know we're looking at a few milliseconds to detect failure and then maybe up around three seconds to actually affect the failover. So the applications that are not getting disconnected, they continue operating in the, in that kind of condition. So that's kind of unique to the Exadata platform. And so, you know, in our cloud, we're running Exadata. We have this built in there. So we're, we're resilient to that type of failure, so. >> And sorry, you mentioned real application clusters. You're saying because you're running real application clusters that's how you're able to become more resilient? >> So yeah, so we have, so Oracle database real application clusters runs on top of a clustered virtual machines on Exadata. We have integration then optimizes the fail over times of that clustering. So it's, it's not the cluster same, it's the optimizations are only built into Exadata. So we have much much faster, much better tighter integration, so much more scalability because of that, that integration that we have. >> Can I run rack in other clouds? Can I put that into Amazon's cloud? >> So, so real application clusters requires two things. It's a, you require shared storage in a fast interconnect, a fast networking interconnecting. And those things just don't exist in the other clouds. We have those built into Exadata in our cloud. And we also, we also allow real application clusters in our relational database, our database cloud service offering as well. But it's, really the highest implementation of that is in Exadata. >> Well, of course I was tongue in cheek joking but this is, this is why, you know, I was listening to Arvind Krishna the other day in IBM Think. And he was saying only 25% of mission critical applications have moved into the cloud. I didn't think it's that high. I mean, but, but what you're doing is basically building a mission critical, you know, cloud or a cloud for mission critical databases. And that's, that's unique. I mean, I would expect other cloud vendors that eventually you know, are going to get there, but you're kind of starting with the hard stuff and working backwards. But, that is what I've always interpreted is unique to Oracle, but how does that affect cost? Isn't that more expensive? >> Actually, no. We're taking services that that start out at a very similar price point. And then we drive. So what we've seen from other customers that are running in like Amazon, for example, we see databases on dedicated virtual machines that run anywhere from 15 to 20% utilization. So what we do is, that low, low utilization, what we do is take that and triple that. So we run, so we run maybe 50% utilization. At that point we still have full redundancy, but we've now made the service one third of the cost. So we're starting at a third, we're starting at a very similar cost. And then we drive it to, you know three times a utilization. This is not crazy numbers. This is, you know, 50% is, is fine and retain the redundancy at that level as well. >> Got it, well so. >> What we've seen is about a third the cost. >> Really? Okay. Well, so, but, what about, like for instance, on AWS, couldn't I run this in a multi availability zone, running RDS or some other cloud database? >> So, so you can run a Multi-AZ environment like in in Amazon, for example, you can run locals. That's what we call local standby. If you do that, you're now instead of being one third, instead of being three times more expensive, you're now six times more expensive. Because that is another copy of the entire platform, the entire instance, the storage, everything on the other availability zone instead of being three times more, it's now six. >> Because you're essentially replicating everything in a brute force mode, right? >> Yeah. It's a data guard standby, local standby in another AZ, or what we call availability domain in our cloud. >> So let's maybe geek out a little bit. So, let's talk more about availability. You know, for years, I mean, I remember going back to reading about this stuff with tandem computers, you know, coincident failures. How are you dealing with those in today's modern world? >> So what we call simultaneous failures is, so we, we deal with that with redundancy in the system. So we have redundancy at all layers in the storage. Like I said earlier, we can take across, you know, two storage cells and each storage cell has a dozen drives. So that's 24 disc drives. That's eight flashcard failures simultaneously. And we keep on running no data loss, no loss of service. That's at the storage layer. We have multiple, multiple redundant networking switches at that, at the networking layer, the internal network. Then we go up into the database server. We then have redundancy across the nodes of a cluster. You have multiple virtual machines that comprise a virtual cluster. So it's at each and every level, we have redundancy. And then we drive the redundancy into the application using what's called application continuity. So the application connections have knowledge of the failure, failure modes of the database. They can follow to the surviving node, and continue operating. >> And you do this with math, you're doing some kind of magic bit slicing, or how do you do that? >> That, so that is that particular thing, application continuity, so technology that's been built into Oracle database since, since 12c, and that it's been around for quite a long time. And it allows the application to follow the rack cluster, any kind of issues with the rack cluster. We can drain connections off. It's very well-proven technology in, you know, prior to to proactive maintenance, we can drain connections over and then it will also handle a failure of a connection as well. And the application following that, yes. >> I learned from my old mainframe days and hanging around with David Floyer. It's always ask, what happens when something goes wrong and it's all about recovery. And you guys have the gold standard there. I mean, we've talked about this a lot. So you got Exadata. That's what is behind your Exadata cloud service, X8M I think you call it, and you've got autonomous database. I'm not great with model numbers, but, but talk about the way you can handle simultaneous failures. I mean, are there like triple redundancies that you've built in? >> Yeah. So everything what we do in our cloud is everything is triple redundancy by default. So we, you can suffer, that way we can suffer two failures and continue operating. So the, the other thing, so recovery, if you look at transaction recovery, when a failure occurs a transaction will flip that session, will flip to the machine that keeps running. It'll reposition all in the work that's in flight, any kind of inflight transactions, any in flight queries that are going on, reposition and continue operating. >> So you've essentially created like the old three site data centers, but you're in a single platform because you're synchronous. But, that same concept in a package. >> It's, you know, it's a lot of times you show a picture of an Exadata. It looks like a single box, but in the box there's some redundancy built in the box. And in fact, in the cloud it's actually across an entire aisle. So it's, we kind of obscure that a little bit, from your provisioning, you know, our database nodes and our storage cells and in the cloud but it's actually across an entire aisle of a dataset. >> Okay, and of course, that's within a synchronous location. Let's talk about disaster recovery, and what you're doing in that area, around Oracle Cloud What are my options there? What's different from other cloud providers we were talking earlier about, AZs, how are you different and what are you doing there? >> Yeah, so we, we talked earlier about the Multi-AZ deployment, what we call it availability domain, AD, so a little different terminology. But we can deploy another, another copy of the database into another availability domain, if you like. It's not often that you lose an entire AZ or AD, it's more, we're protecting from regional failures. So across another region. And that's where we look at, we really look at that as that technology, as a standby, as a data, disaster recovery solution not for HA. HA, we build HA into the machine itself. >> So you're saying, we were talking earlier about AZ, you're saying that's for HA versus DR. Is that, is that what you're contending? >> Yeah, like, you know again, pick on Amazon for a second here. Amazon uses a standby database. What we would normally use for disaster recovery, they're using that for availability. And you're looking at a few minutes of time to flip over to another AZ, whereas within an Exadata frame, we can flip over in milliseconds. We keep continue running. There is no loss of conductivity. And then we use the standby in another region for disaster. That's a true disaster solution. >> As opposed to incurring that penalty of latency, or whatever, to spin up the other resource. >> Right, right. >> Okay, so that's clear how kind of you guys address that, that challenge. Last question, maybe you could give us your take, again folks, coming out of Oracle's mouth, but what's the bottom line cost Delta based on your experience between your service and competitive services? I love these conversations because you're not afraid to talk about the competition, so bring it on. >> I've seen, so we've just based on what we've seen with customers deploying databases in Amazon, versus what, you know we've replaced that within, in our cloud service. We're seeing from just a list price perspective. Now, you know, we discount, I know Amazon discounts, but the only thing I can really speak to is list price perspective. It's about a third the cost. So we're talking about a more powerful platform, runs faster. We get these incredible, we haven't even talked about performance here. Talk about availability, performance where we're getting IO rates, IO latencies in the 19 microsecond range. Now with Exadata, that's going to be 50 times faster than what you get with these traditional cloud vendors. So much, much faster, and a third the cost. >> So talk about discounts, I mean, I know Oracle discounts, Oracle from list price, Oracle provides significant discounts. I'm not as familiar with your cloud pricing but I mean, Amazon's discounts are really in the form of like reserved instances. Is your pricing similar in that regard or different? I mean, if I'm just paying on demand, I'm paying through the nose. I presume it's same with you. If I, but if I buy in bulk getting a discount, is that what you mean by discount? Or is it more similar to the way you've traditionally discounted, you know large customers, the more you spend, the more you you get kind of thing. >> It's a, there's a discount structure. So it's, we don't have the same kind of lock-in like with reserved instance structure, but yeah, it's, there are discounts and that's going to be very customer specific. >> Right. >> So, but I think that the end result we're starting at, a three X differential on the price. >> But the reason I'm asking the question is that the stats you gave me are for list price, right? >> Yeah, yes, yeah. >> Okay, and sure, you're saying that at list price you're, you're less expensive. I, and again, my contention would be just by experiences that your discounts would be more aggressive traditionally in Oracle's traditional business. You know, I've done a lot of Oracle negotiation in my days. And if you're, you know, if you're a big customer you can get good deals. And again, I'm not as familiar with the cloud pricing, but still that's, that's good. If you're doing it on a list price basis, to me, that's a conservative statement if that makes any sense. >> Right, that's where it starts. We know that's where it's starting out. So I, you know, once you get into discounts, it's very customer specific. >> Right. >> We know the starting point is at three X differential. Before you do something in the Multi-AZ would be a six X differential, by the way, so. >> Yeah, okay. All right, Chris. Well, Hey, I appreciate you taking us through this, good stuff, and best of luck, good work. You know, you guys keep, I always say Oracle invest you guys spend a lot of money in RD and, and, you know you're quiet for a while in the cloud and all of a sudden you came out like you invented it. So good job! >> All right. >> All right, thanks. Thanks for coming on. All right. >> Thanks. >> Thank you for watching everybody. This is Dave Vellante for Cube conversations. We'll see you next time. (upbeat music)

>> From Boston, Massachusetts, it's theCUBE! Covering Actifio 2019 Data Driven. Brought to you by Actifio. >> Here we are in Boston, Massachusetts. I'm Stu Miniman, this is theCUBE at the special, at Data Driven '19, Actifio's user event. Happy to bring on a CUBE alum who's a partner of Actifio, Phil Buckellew, who's General Manager of IBM Cloud Object Storage. Phil, thanks for coming back. >> Great, great to be here Stu. >> All right, so object storage. Why don't you give us first just kind of an encapsulation of kind of the state of your business today. >> Sure, object storage is really an extremely important business for the industry today because really it's a new way accessing data, it's been around obviously for a decade or so but really, it's increasingly important because it's a way to cost-effectively store a lot of data, to really to be able to get access to that data in new and exciting ways, and with the growth in the volume of data, of particularly unstructured data, like 103 zettabytes by 2023 I think I heard from the IDC guys, that really kind of shows how important being able to handle that volume of data really is. >> So Phil, I go back, think about 12 years ago, all the technologists in this space were like, "The future of storage is object," and I was working at one of the big storage companies and I'm like, "Well we've been doing block and file," and there was this big gap out there, and kind of quietly object's taken over the world because underneath a lot of the cloud services there, object's there, so IBM made a big acquisition in this space. Talk about, you know, customers that I talk to it's not like they come out and say, "Oh jeez, I'm buying object storage, "I'm thinking about object storage." They've got use cases and services that they're using that happen to have object underneath. Is that what you hear from your users? >> Yeah, there's a couple of different buying groups that exist in the object storage market today. The historic market is really super large volumes. I mean, we're unique in that IBM acquired the Cleversafe company back in 2015 and that technology is technology we've expanded upon and it really, it's great because it can go to exabyte scale and beyond and that's really important for certain use cases. So some customers that have high volumes of videos and other unstructured data, that is really a super good fit for those clients. Additionally, clients that really have the need for highly resilient, because the other thing that's important the way that we built our object storage is to be able to have a lot of resiliency, to be able to run across multiple data centers, to be able to use erasure coding to ensure the data's protected, that's really a large part of the value, and because you can do that at scale without having downtime when you upgrade, those are really a lot of core benefits of object storage. >> Right, that resiliency is kind of built into the way we do it and that was something that was just kind of a mind shift as opposed to, okay I've got to have this enterprise mindset with an HA configuration and everything with N plus whatever version of it. Object's going to give you some of that built-in. The other thing I always found really interesting is storing data is okay, there's some value there, but how do I gain leverage out of the data? And there's the metadata underneath that helps. You talk about video, you talk about all these kinds there. If I don't understand what I've got and how I'd leverage it, it's not nearly as valuable for me, and that's something, you know really that one of the key topics of this show is, how do I become data driven, is the show, and that I have to believe is something critically important to your customers. >> Absolutely, and really object storage is the foundation for modern cloud-native data lakes, if you will, because it's cost-effective enough you can drop any kind of storage in there and then you can really get value from those assets wherever you are, and wherever you're accessing the data. We've taken the same technology that was the exabyte scale on-premise technology, and we've put it in the IBM public cloud, and so that really allows us to be able to deliver against all kinds of use cases with the data sets that clients want, and there's a lot of great innovation that's happening especially on the cloud side. We've got the ability to query that data, any kind of rectangular data with standard ANSI SQL statements, and that just really allows clients to unlock the potential of those data sets, so really good innovation going on in that space to unlock the value of the data that you put inside of object storage. >> All right, Phil let's make the connection. Actifio's here, IBM OEM's the solution. So, talk about the partnership and what customers are looking for when they're looking at their IPs. Sure, so, quite a ways prior to the partnership our object storage team partnered up with the Actifio team at a large financial services customer that recognized the growth in the volume of the data that they had, that had some unique use cases like cyber resiliency. They get attacked with ransomware attacks, they needed to have a standard way to have those data sets and those databases running in a resilient way against object storage that can still be mounted and used, effectively immediately, in case of ransomware attacks, and so that plus a lot of other traditional backup use cases is what drew the IBM Cloud Object Storage team and the Actifio team together. Successful deployments at large customers are really where we got our traction. And with that we also really began to notice the uptick in clients that wanted to use, they wanted to do test data management, they wanted, they needed to be able to have DevOps team that needed to spin up a replica of this database or that database very fast, and, you know, what we found was the combination of the Actifio product, which we've OEM'd as IBM Virtual Data Pipeline, allows us to run those virtual databases extremely cost-effectively backed by object storage, versus needing to make full replicas on really expensive block storage that takes a long time. >> Well yeah, we'd actually done research on this a number of years ago. Copies are great, but how do I leverage that right? From the developer team it's, I want to have something that mirrors what I have in production, not just some test data, so the more I can replicate that, the better. Phil, please, go ahead. >> There's some really important parts of that whole story, of being able to get that data flow right, to be able to go do point-in-time recoveries of those databases so that the data is accurate, but also being able to mask out that PII or sensitive information, credit card data or others that you really shouldn't be exposing to your testers and DevOps people. Being able to have the kind of-- (Phil laughs) >> Yeah, yeah, shouldn't because, you know, there's laws and lawsuits and security and all these things we have. >> Good, good, absolutely. >> So, Phil, we're talking a lot about data, you've actually got some new data to share with us, a recent survey that was done, should we share some of your data with us? >> Yeah, we did some, we did a, the ESG guys actually worked with us to build out a piece of research that looked at what would it cost to take a 50 terabyte Oracle 12c database and effectively spin up five copies the way you traditionally would so that different test teams can hammer away against that data set. And we compared that to running the VDP offering with our Cloud Object Storage solution. You know, distances apart, we had one where the source database is in Dallas and the destination database is in Washington, D.C. over a 10 gigabyte link, and we were able to show that you could set up five replicas of the database in like 90 minutes, compared with the two weeks that it would take to do full replication, because you were going against object storage, which runs about 2.3 cents per gigabyte per month, versus block storage fully loaded, which runs about 58 cents per gigabyte per month. The economics would blow away. And the fact that you could even do queries, because object storage is interesting. Yes, if you're using, if you have microsecond response times for small queries you got to run some of that content on block storage, but for traditional queries, we look at, like, really big queries that would run against 600 rows, and we were half the time that you would need on traditional block storage. So, for those DevOps use cases where you're doing that test in development you can have mass data, five different copies, and you can actually point back in time because really, the Actifio technology is really super in that it can go do point-in-time, it was able to store the right kind of data so the developers can get the most recent current copies of the data. All in, it was like 80% less than what you would have paid doing it the traditional way. >> Okay, so Phil, you started talking a little bit about some of the cloud pieces, you know, Actifio in the last year launched their first SaaS offering Actifio GO. How much of these solutions are for the cloud versus on-premises these days? >> Absolutely, so one of the benefits of using a virtual data approach is being able to leverage cloud economics 'cause a lot of clients they want to do, you know, they want to be able to do the test in dev which has ups and downs and peaks and valleys when you need to use those resources, the cloud is really an ideal way to do those types of workloads. And so, the integration work that we've done with the Actifio team around VDP allows you to replicate or have virtual copies of those databases in the cloud where you want to do your testing, or we can do it in traditional on-prem object storage environments. Really, whatever makes most sense for the client is where we can stand up those environments. >> The other thing I wonder if you could expand on a little bit more, you talked about, like, cloud-native deployment and what's happening there. How does that tie into this discussion? >> Well, obviously modern architectures and ways of Agile, ways of building things, cloud-native with microservices, those are all extremely important, but you've got to be able to access the data, and it's that core data that no matter how much you do with putting Kubernetes around all of your existing applications you've still got to be able to access that core data, often systems record data, which is sitting on these standard databases of record, and so being able to have the VDP technology, be able to replicate those, stand those up like in our public cloud right next to all of our Kubernetes service and all the other technologies, it gives you the kind of full stack that you need to go do that dev in test, or run production workloads if you prefer from a public cloud environment, without having all of the burdens of running the data centers and maintaining things on your own. >> Okay, so Phil, everybody here for this two day event are going to get a nice, you know, jolt of where Actifio fits. You know, lots of orange here at the show. Give us the final word of what does it mean with orange and blue coming together. >> Well absolutely, we think this is going to be great for our clients. We've got, you know, tons of interested clients in this space because they see the value of being able to take what Actifio's done, to be able to virtualize that data, combine it with some of the technologies we've got for object storage or even block storage, to be able to serve up those environments in a super cost-effective way, all underlined by one of our core values at IBM, which is really trust and being responsible. And so, we often say that there's no AI, which all of this data leads up to, without information architecture and that's really where we specialize, is providing that governance, all the masking, all of the things that you need to feel confident that the data you've got is in the right hands, being used the right way, to be able to give you maximum advantage for your business, so we're super excited about the partnership. >> Phil, definitely a theme we heard at IBM Think, there is no AI without the IA, so, Phil Buckellew, thanks so much for joining us, sharing all the updates on what IBM is doing here with Actifio. >> Great, great to be here. >> All right, and we'll be back with more coverage here in Boston, Massachusetts at Actifio Data Driven 2019. I'm Stu Miniman and thanks for watching theCUBE. (futuristic music)

>> Announcer: Live from Washington D. C., it's the CUBE. Covering .conf2017. Brought to you by Splunk. (electronic music) >> Welcome back to the nation's capitol everybody. This is the CUBE, the leader in live tech coverage. And we're here at day two covering Splunk's .conf user conference #splunkconf17, and my name is Dave Vellante, I'm here with with co-host, George Gilbert. As I say, this is day two. We just came off the keynotes. I'm over product orientation today. George, what I'd like to do is summarize the day and the quarter that we've had so far, and then bring you into the conversation and get your opinion on what you heard. You were at the analyst event yesterday. I've been sitting in keynotes. We've been interviewing folks all day long. So let me start, Splunk is all about machine data. They ingest machine data, they analyze machine data for a number of purposes. The two primary use cases that we've heard this week are really IT, what I would call operations management. Understanding the behavior of your systems. What's potentially going wrong, what needs to be remediated. to avoid an outage or remediate an outage. And of course the second major use case that we've heard here is security. Some of the Wall Street guys, I've read some of the work this morning. Particularly Barclays came out with a research note. They had concerns about that, and I really don't know what the concerns are. We're going to talk about it. I presume it's that they're looking for a TAM expansion strategy to support a ten billion dollar valuation, and potentially a much higher valuation. It's worth noting the conference this year is 7,000 attendees, up from 5,000 last year. That's a 40% increase, growing at, or above actually, the pace of revenue growth at Splunk. Pricing remains a concern for some of the users that I've talked to. And I want to talk to you about that. And then of course, there's a lot of product updates that I want to get into. Splunk Enterprise 7.0 which is really Splunk's core analytics platform ITSI which is what I would, their 3.0, which I would call their ITOM platform. UBA which is user behavior analytics 4.0. Updates to Splunk Cloud, which is a service for machine data in the cloud. We've heard about machine learning across the portfolio, really to address alert fatigue. And a new metrics engine called Mstats. And of course we heard today, enterprise content security updates and many several security-oriented solutions throughout the week on fraud detection, ransomware, they've got a deal with Booz Allen Hamilton on Cyber4Sight which is security as a service that involves human intelligence. And a lot of ecosystem partnerships. AWS, DellEMC was on yesterday, Atlassian, Gigamon, et cetera, growing out the ecosystem. That's a quick rundown, George. I want to start with the pricing. I was talking to some users last night before the party. You know, "What do you like about Splunk? "What don't you like about Splunk? "Are you a customer?" I talked to one prospective customer said, "Wow, I've been trying to do "this stuff on my own for years. "I can't wait to get my hands on this." Existing customers, though, only one complaint that I heard was your price is to high, essentially is what they were telling Splunk. Now my feeling on that, and Raymo from Barclays mentioned that in his research note this morning. Raymo Lencho, top securities analyst following software industry. And my feeling George is that historically, "Your price is too high," has never been a headwind for software companies. You look at Oracle, you look at ServiceNow, sometimes customers complain about pricing too high. Splunk, and those companies tend to do very well. What's your take on pricing as a headwind or tailwind indicator? >> Well the way, you always set up these questions in a way that makes answering them easy. Because it's a tailwind in the sense that the deal sizes feed an enterprise sales force. And you need an enterprise sales force ultimately to be pervasive in an organization. 'Cause you can't just throw up like an Amazon-style console and say, "Pick your poison and put it all together." There has to be an advisory, consultative approach to working with a customer to tell them how best to fit their portfolio. >> Right. >> And their architecture. So yes, the price helps you feed that what some people in the last era of enterprise software used to call the most expensive migratory workforce in the world., which is the sales, enterprise sales organization. >> Sure, right. >> But what's happened in the different, in the change from the last major enterprise applications, ERPCRM, and what we're getting into now, is that then the data was all generated and captured by humans. It was keyboard entry. And so there was no, the volumes of data just weren't that great. It was human, essentially business transactions. Now we're capturing data streaming off everything. And you could say Splunk was sort of like the first one out of the gate doing that. And so if you take the new types of data, customer interactions, there are about ten to a hundred customer interactions for every business transaction. Then the information coming out of the IT applications and infrastructure. It's about ten to a hundred times what the customer interactions were. >> Yeah. >> So you can't price the, Your pricing model, if it stays the same will choke you. >> So you're talking about multiple orders of magnitude >> Yes. >> Of more data. >> Yeah. >> And if you're pricing by the terabyte, >> Right. >> Then that's going to cross your customers. >> Right. But here's what I would argue though George. I mean, and you mentioned AWS. AWS is another one where complaints of high pricing. But if, to me, if the company is adding value, the clients will pay for it. And when you get to the point where it becomes a potential headwind, the company, Oracle is a classic at this, will always adjust its pricing to accommodate both its needs as a public organization and a company that has to make money and fund R & D, and the customers needs, and find that balance where the competition can't get in. And so it seems to me, and we heard this from Doug Merritt yesterday, that his challenge is staying ahead of the game. Staying, moving faster than the cloud guys. >> Yeah. >> In what they do well. And to the extent that they do that, I feel like their customers will reward them with their loyalty. And so I feel as though they can adjust their pricing mechanisms. Yeah, everybody's worried about 606, and of course the conversions to subscriptions. I feel as though a high growth, and adjustments to your pricing strategy, I think can address that. What do you think about that? >> It's... It sounds like one of those sayings where, the friends say, "Well it works in practice, "but does it work in theory?" >> No, no. But it has worked in practice in the industry hasn't it? So what's different now? >> Okay. So take Oracle, at list price for Oracle 12C, flagship database. The price per processor core, with all the features thrown in, is something like three hundred thousand, three hundred fifty thousand per core. So you take an average Intel high end server chip, that might have 24 cores, and then you have two sockets, so essentially one node server is 48 times 350. And then of course, Oracle will say, "But for a large customer, we'll knock 90% off that," or something like that. >> Yeah, well exactly. >> Which is exactly what the Splunk guys told me yesterday. But it's-- >> But that's what I'm saying. They'll do what they have to do to maintain the footprint in the customer, do right by the customer, and keep the competition out. >> But if it's multiple orders of magnitude different. If you take the open source guys where essentially the software's free and you're just paying for maintenance. >> (laughs) Yeah and humans. >> Yeah, yeah. >> Okay, that's the other advantage of Splunk, as you pointed out yesterday, they've got a much more integrated set of offerings and services that dramatically lower. I mean, we all know the biggest cost of IT is people. It's not the hardware and software but, all right, I don't want to rat hole on pricing, but that was a good discussion. What did you learn yesterday? You've sat through the analyst meeting. Give us the rundown on George Gilbert's analysis of .conf generally and Splunk as a company specifically. >> Okay, so for me it was a bit of an eye opener because I got to understand sort of, I've always had this feeling about where Splunk fits relative to the open source big data ecosystem. But now I got a sense for what their ambitions are, and what their tactical plan is. I've said for awhile, Splunk's the anti-Hadoop. You know, Hadoop is multiple, sort of dozens of animals with three zookeepers. And I mean literally. >> Yeah. >> And the upside of that is, those individual projects are advancing with a pace of innovation that's just unheard of. The problem is the customer bears the burden of putting it all together. Splunk takes a very different approach which is, they aspire apparently to be just like Hadoop in terms of platform for modern operational analytic applications, but they start much narrower. And it gets to what Ramie's point was in that Wall Street review, where if you take at face value what they're saying, or you've listened just to the keynote, it's like, "Geez, they're in this IT operations ghetto, "in security and that's a La Brea tar pit, "and how are they ever going to climb out of that, "to something really broad?" But what they're doing is, they're not claiming loudly that they're trying to topple the giants and take on the world. They're trying to grow in their corner where they have a defensible moat. And basically the-- >> Let me interrupt you. >> Yeah. >> But to get to five billion >> Yeah. >> Or beyond, they have to have an aggressive TAM expansion strategy, kind of beyond ITOM and security, don't they? >> Right. And so that's where they start generalizing their platform. The data store they had on the platform, the original one, is kind of like a data lake in the sense that it really was sort of the same searchable type index that you would put under a sort of a primitive search engine. They added a new data store this time that handles numbers really well and really fast. That's to support the metrics so they can have richer analytics on the dashboard. Then they'll have other data stores that they add over time. And for each one, you're able to now build with their integrated tool set, more and more advanced apps. >> So you can't use a general purpose data store. You've got to use the Splunk within data. It's kind of like Work Day. >> Yeah, well except that they're adding more over time, and then they're putting their development tools over these to shield them. Now how seamlessly they can shield them remains to be seen. >> Well, but so this is where it gets interesting. >> Yeah. >> Splunk as a platform, as an application development platform on which you can build big data apps, >> Yeah. >> It's certainly, conceptually, you can see how you could use Splunk to do that right? >> And so their approaches out of the box will help you with enterprise security, user, they call it user behavior analytics, because it's a term another research firm put on it, but it's really any abnormal behavior of an entity on the network. So they can go in and not sell this fuzzy concept of a big data platform. They said, they go in and sell, to security operations center, "We make your life much, much easier. "And we make your organization safer." And they call these curated experiences. And the reason this is important is, when Hadoop sells, typically they go in, and they say, "Well, we have this data lake. "which is so much cheaper and a better way "to collect all your data than a data warehouse." These guys go in and then they'll add what more and more of these curated experiences, which is what everyone else would call applications. And then the research Wikibon's done, depth first, or rather breadth first versus depth first. Breadth first gives you the end to end visibility across on prem, across multiple clouds, down to the edge. But then, when they put security apps on it, when they put dev ops or, some future big data analytics apps as their machine learning gets richer and richer, then all of a sudden, they're not selling the platform, because that's a much more time-intensive sale, and lots more of objectives, I'm sorry, objections. >> It's not only the solutions, those depth solutions. >> Yes, and then all of a sudden, the customer wakes up and he's got a dozen of these things, and all of a sudden this is a platform. >> Well, ServiceNow is similar in that it's a platform. And when Fred Luddy first came out with it, it's like, "Here." And everybody said, "Well, what do I do with it?" So he went back and wrote a IT service management app. And they said, "Oh okay, we get it." Splunk in a similar way has these depth apps, and as you say, they're not selling the platform, because they say, "Hey, you want to buy a platform?" people don't want to buy a platform, they want to buy a solution. >> Right. >> Having said that, that platform is intrinsic to their solutions when they deliver it. It's there for them to leverage. So the question is, do they have an application developer kit strategy, if you will. >> Yeah. >> Whether it's low code or even high code. >> Yeah. >> Where, and where they're cultivating a developer community. Is there anything like that going on here at .conf? >> Yeah, they're not making a big deal about the development tools, 'cause that makes it sound more like a platform. >> (laughs) But they could! >> But they could. And the tools, you know, so that you can build a user interface, you can build dashboards, you can build machine learning models. The reason those tools are simpler and more accessible to developers, is because they were designed to fit the pieces underneath, the foundation. Whereas if you look at some of the open source big data ecosystem, they've got these notebooks and other tools where you address one back end this way, another back end that way. It's sort of, you know, you can see how Frankenstein was stitched together, you know? >> Yeah so, I mean to your point, we saw fraud detection, we saw ransomware, we see this partnership with Booz Allen Hamilton on Cyber4Sight. We heard today about project Waytono, which is unified monitoring and troubleshooting. And so they have very specific solutions that they're delivering, that presumably many of them are for pay. And so, and bringing ML across the platform, which now open up a whole ton of opportunities. So the question is, are these incremental, defend the base and then grow the core solutions, or are they radical innovations in your view? >> I think they're trying to stay away from the notion of radical innovation, 'cause then that will create more pushback from organizations. So they started out with a google-search-like product for log analytics. And you can see that as their aspirations grow for a broader set of applications, they add in a richer foundation. There's more machine learning algorithms now. They added that new data store. And when we talked about this with the CEO, Doug Merritt yesterday at the analyst day, he's like, "Yes, you look out three to five years, "and the platform gets more and more broad. "and at some point customers wake up "and they realize they have a new strategic platform." >> Yeah, and platforms do beat products, and even though it's hard sell, if you have a platform like Splunk does, you're in a much better strategic position. All right, we got to wrap. George thanks for joining me for the intro. I know you're headed to New York City for Big Data NYC down there, which is the other coverage that we have this week. So thank you again for coming on. >> Okay. >> All right, keep it right there. We'll be back with our next guest, we're live. This is the CUBE from Splunk .conf2017 in the nation's capitol, be right back. (electronic music)

but cute at servicenow knowledge 14 is sponsored by service now here are your hosts Dave vellante and Jeff trick we're back welcome everybody Alan line wind is here he's the vice president and chief technology officer of the cloud platform and infrastructure components of service now all the stuff that you don't see it's sort of behind the curtains all the magic and the secret sauce Alan welcome to the cube thank you very much for everything so what's the what's going on what's new in the in the cloud platform you guys obviously started this before cloud was sort of even referred to yes cloud you know I mean I mean Fred talks about his vision and sore clouds in there but you know really cloud started mid-2000s 2006 and then really started taking off so the latter part of the decade you guys kind of maybe not predated but so the same time you know so what's how was the platform evolved I mean the platform is really evolved during people like to talk about cloud when I think about cloud that's a little bit beyond water vapor so what we end it's been a hard time doing the very early to make silicon and make aluminum actually perform something for our customers the cloud platform has really evolved into being a platform that allows people to develop applications that are either both for IT or for the entire enterprise that's really what we're sort of here to talk about from service now is perspective in this whole show is what we've done on the platform is beyond IT and it can power services for the whole enterprise so we've scaled our cloud significantly we're in eight different regions across the planet 16 different data center locations and we're continuing to grow globally on our cloud right now so these data center locations that you used to you're building out data centers you we're actually using wholesale and retail space so we're using our data center partners and we're building out large cases of infrastructure that we own and operate on our own okay so so just make sure I understand so you're not building mega data centers yeah that's not your strategy that's right can you talk about why that's not strategy yeah I mean we're not building on mega datacenters like maybe they hear from facebook and google or other folks we're actually using our data center partners to build the infrastructure sort of meet our customer needs we don't necessarily host people or do sort of infrastructure services like those guys do we end up doing is we're in a building very specific cloud platforms in restructure for the enterprise it just turns out a footprint for that just isn't as big as other folks and we scale it as we need to do and there's confusion also about and I wonder if you could help us clear it up you're sort of your approach to multi-tenancy let's chat all right so you don't have a multi-tenancy that's remodel you've got more of a hybrid model can you talk about that a little bit and what the advantages are yeah absolutely there's folks that have a multi-tenant model what that really means is that multiple customers data is interlaced and and are intersected with in the same data structures within the same data sounds scary it is and can do that scary but we've actually ended up doing is segmenting both the application logic into virtual machines per customer and then actually dividing up the database itself on a per customer basis or every one of our customers has their own unique database process unique to them their own tables their own data they're on isolation and they have application luggages that's unique to them as well that's very different from multi-tenancy where you have a large database and a large piece of infrastructure that a lot of people share one of the biggest advantages for that for our customers is really about availability if I'm a big huge multi-tenant architecture I need to take all hundreds and hundreds of customers in this pod and move them somewhere else because of a failure that's a scary operation but we actually have the ability to do is move individual customers around our cloud and provide a very high available solution for them because of the fact in the way we've architected so if I'm a customer and and you're on a sales call and you tell me that I'm I good I want that right I'm like totally cool with that I'll tell you something right now if ok now if i'ma we're not quite big enough yet although there's some new products are coming up appeal to us but now if I'm let's say I'm an investor I might say well jeez aren't I going to get better leverage if I go multi-tenancy think Amazon and some of you know larger players also that response to that yeah I mean that's sort of an interesting distinction when people think about multi-tenancy their verses single term see what we call it what you actually find is that they think that the multi-tenancy allows you to scale the hardware better but the truth is what we've done when we actually called multi-instance is a hardware can be shared but the actual customer deployment the Java Virtual Machine the database for that customer is laid down on that shared harders we're actually getting good economics at the hardware and we're giving customers isolation they want we think it's very unique in industry loss is just really exciting things well we heard actually was interesting at oracle openworld which was here i want to say two years ago yeah so it was 2012 maybe was even 2011 was 2011 Ellison really railed on multi-tenancy yeah he railed on work day he railed on on on salesforce and said multi-tenancy is a bad thing you don't want to do it in the application now I think I know 12c changes that I'm not sure I know he did a flip flop Larry does that a lot but um but but your your your your dogma if you will is not going to flip flop rights right you guys got you you can see this am I correct well let me ask you does the scale you know to you know huge Heights that Frank's lubin once they hit yeah I mean we have 11,000 12,000 customer instances in the clouds individual instantiations but let me give you a quick fact here for knowledge we spun out 23,000 additional instances so we have the ability to scale this model in a very dynamic way and a very well orchestrated way we think it really helps our customers one of these I like to say about multi-tenancy is I get why it's good for the cloud provider I get why the folks that build multi-tenancy build it because you're right it you both at once you carve it up or bunch of pieces for a customer customers data is interlaced okay I'm not sure why I want that as a customer customer wants out isolation that's what we provide well giving both leverage of hardware and isolation of data yeah because again a conceptual you can see how there might be some some margin advantages but then then the big question to me a security sure know what kind of what kind of security nuance wants not the right word does it ease the security requirements does it make your security cleaner you know easier to scale replicate etc you talked about that a little yeah I mean it clearly makes our application logic easier because they viewed portion of the application is talking to that individual database instance for that individual customer but our security focus is really focused on protecting those instances from the various threats so we're always looking at threats on the Internet we're always adding our perimeter firewalls we're already doing our third party audits we're doing a penetration test so just like any other cloud provider we're continually updating our security model and making sure we're advancing and trying to stay one step ahead of bad guys but because we have customer data that is segmented and isolated it does make our security model easier and more straightforward for the customer by using a lot of open source in the back end yeah we do do a bunch of my soup of open source for the databases of course right we do a bunch of apology on the front end using Mongo right we are using Mongo to help us get our document store for a larger customers that's right what kind of effect if any did heartbleed have on you guys yeah we looked at heart bleed and we we looked at the effect of it we didn't really see much in effect we weren't using systems are affected by that yeah awesome so Alan we've been covering a lot of data center stuff absolutely and there's a lot of interesting innovation that's happening in the infrastructure we're cooling and our and segmentation and all kinds of interesting things where's the line of innovation in the data center between your stuff and the infrastructure provided that you're working with yeah so we spend a lot of time actually focused on the actual sort of server platform storage platform communication between the web servers in the network we don't spend a lot of time on maybe hot aisle containment or cold out containment worried about you know efficiency of the building or air flow through the building we spend a lot of time sort of utilizing the best practices there so we go look for our data center providers that are really driving that peewee number down to the level 10 level but we're not architecting the building we'll look for those providers and then we'll deploy our equipment in a way that takes advantage of that you know we're following and using some of the practices from local compute we're looking at the next generation networking hardware and networking software that's out there and we're really sort of leveraging everything that they're building on the data center itself and then I know there's a lot of data data regulations that are driving kind of the location of your data centers or where he says you have 16 that's right they're basically at eight locations double located that's where if I recall a country's yeah yep so there's still some some open area that you need to penetrate based on customer and demand that you haven't gone yet or where the next one's going to be yeah we're going to build with the customers ask us to build we built into Switzerland and Geneva and Zurich because of that we built in a Canada for data sovereignty issues we're building into Brazil we're building in Asia right now Hong Kong and Singapore so we're going to kind of go over the customer demand takes us oh it's a big question on on Germany and this came up actually we're at the AWS reinvent we did the age of aw our summit and Amazon doesn't have a data center in Germany sure don't have a data we do not turn out right but of course everybody knows german law but everybody knows but but the the sort of urban legend is German losses you got a store data in Germany when we asked amazon this they said well we have a location in ireland that's part of the EU is that a similar response that you guys track we have amsterdam and london and we serve the EU countries ramps down so if I'm a German customer I would store my data there yeah right I mean that would be the default I mean we actually might have a German customer that want to be in the US but we actually had our customers pick which region of the world that want to be deployed in and we deploy on their behalf in there that's a prerequisite of going through the process right you use wage in a store your data that's right and then that's a sales guys figure that out so I so I asked actually i'll ask you as well the Amazon perspective has that ever been tested you know in the court of law do we actually know that this stands up cuz you always hear so much from the the anti amazon crowd oh well you can't choose where your data is stored that's not true certainly not true with you that's right and Germany Brazil very strict they actually have a location in Brazil but but so are you comfortable that it's consider compliant with German law and in this instance do you have those conversations or customers I mean obviously you do business in Germany yeah i mean i'll say my last name is Austrian German but I'm not well-versed in German like everything people tell me I know we can deploy and it's always a good answer without a lawyer okay I am NOT a liar but it's not stopping sales right not something i mean i've seen this again there's so much chatter and noise out there yeah but none of those misperceptions people like to throw that thought out there they like to say you can't do business I haven't had that objection I'm sure we may run into it but right now it's not top of mind good it was interesting it at a pro Conal i would actually had a lawyer on Richard on every often on the Cuban he said you know there's even different data laws in Massachusetts from Connecticut you know Mike well where is the data I mean especially the cloud and is distributed you're talking about across state borders and it hasn't really been challenged and it apparently it hasn't yet or it's going to get really nasty because cloud just by its very nature stuffs distributed that's right it's replicated it's all over the place so it's everywhere from so everybody uses Germany but he was talking about the difference between two borders border states so it could be interesting at some point in time should we talked earlier about my sequel was really was surely the the data platform that you started that's right and then Mongo came in recently didn't it within a year or two we end up doing is we we deploy the master database so the reads and writes in my sequel we also have capabilities in the platform that when we start to scale the hardware we can add what's called we replicas so we can add sort of versions of my sequel that can take transactions that are read-only and then for people that have large document stores you're doing attachments are doing forums are doing images things are really document-based we can actually deploy Mongo and then we can use Mongo for that particular type of transaction in that system as well so that's what you use in long ago that's okay that wasn't clear to me and that's relatively new initiative is it not yeah came out in Calgary which was last year was that release right okay member i'm talking about it last year i think it at no 13 that's right okay so what's what's next for you guys you know behind the curtain which I it's not really behind the curtain many customers would say if I'm hurting right now that's it but you guys didn't you know it's not like is this is a mean well I guess it is party in marketing but you know you don't be talking about products you're talking about value but it's great we have an opportunity to speak to guys like you actually you know running the factory right yeah so what's next what's what a customer is asking for what are the innovations that you guys are working on yeah i think what customers are really asking for is for us to take the cloud platform in the infrastructure and really to evolve it to be that hardened highly available persistent you know people want to talk about the cloud being like electricity being always on we obviously strive for that but like any other business we we have issues you know hardware does go break and we does booming overnight we have to make sure we perfect it we're constantly tuning that we're focused very much on availability you'll see something tomorrow we're actually going to show customers their individual availability as opposed to this sort of larger distributed availability if you will talk about we're also looking into more automation so that way things that generally break that we now have humans intervene with we want to have that automation kick off automatically and then have people automatically have have the machines do that automatically instead of the humans and we're spending a lot of time just really focused on keeping the cloud alive keeping the cloud available and making sure it is kind of behind the curtain yeah invisible is always good right you know I asked Fred this morning and I'll ask you cuz I didn't fully grasp the answer and I want to want to get pressing at this fred was maybe a little over my head or was i don't know maybe I just didn't get it but so the question I had is so you're not really like the mega data center right we talked about earlier you're not like Amazon or Facebook or Google but you know you're growing you could you're getting to a scale that's quite large and you can you can see you know the future you could be very very large today you've got you know n number of applications it's not overwhelming and the question I ask for fred was working a sort of architecture question in database than the database world you've got transactions you're locking on the database the record that's one one application says I got it and then releases it then the next one has it as you grow out the applications my question the fred was does that become problematic do you get no queuing problems performance issues scale issues and he said his answer if I could summarize and I hope I get this right was especially we're not a heavy locking environment and so on number two there's a lot of other things that go on engagements that go on outside of that lock so you didn't see it as a challenge because of the nature of the applications and and I guess the architecture itself but as you grow to massive scale does that potentially become a problem have you architected around that do you have to architect around that or am I just not understanding it yeah i mean i think if we were multi-tenant where we had thousands of customers sharing a single database doing with those locking issues and the similar issues we'd have that issue but fortunately because every customer gets their own version of their own unique database they're just worried about the applications that they're running so what we end up doing is going to monitoring the hardware and monitoring the databases for transaction rates per customer and as this transaction rates per customer as they add applications as they add users as they're adding joins and lists and building forms and creating services like Fred talked about this morning we can actually find out if their database is starting to see issues and if their particular database to start to see issues we can then go to point B but because we can go deploy things like Mongo on a customer by customer basis so we don't have this Gale issue per se we have the monitor the individual customer transaction rate issue and make sure we're always automating and always upgrading the infrastructure to match yeah ok so you've obviously thought about this problem and the customer has to be quite large to even encounter the problem that's right and then you've got methods techniques approaches even I don't even call it brute force approaches we can we can solve it more silica there are cases where the bigger box wins right yeah Moore's Law wins you can you can add more metal to the clouds so and you can make a bigger so the point of all the reason I'm asking all these questions is not just for sort of you know academic or theoretical cures is there is this a potential constraint to your growth down the road and I'm hearing no it's not yeah we don't see it as a constraint some of our biggest customers are running very very large transaction rates regular scale both the core metal to actually drive those transactions as well as tune the system and tune the way the database behaves that way those interactions you're talking about those locks those joins or select statements can actually be handle by the system in a very efficient manner and what do you make of all this you know it's sort of started at at vmworld a year or so ago with the whole software-defined meme and the acquisition of nice Sarah software-defined networking now they're talking about software-defined storage you certainly see that from the hyperscale guys what do you make of that is that is that how does that affect your world well you're talking to guy that actually worked on a software-defined networking company I founded a company called viata in my path to know Coach brocade actually bought right so I believe in the sufferer Defined Networking I believe that software and algorithms running the metal makes a lot of sense our automation our workflow orchestration tools we have on the platform are what we use to bend our metal in the way we like for our customers and I think really putting logic into the software and learning a software actually change the infrastructure is the way for the future and so thinking about your storage and your network and yours your compute infrastructure you're sort of buying off the shelf that's right standard servers are you buying from ODMs or a combination we do we'd a little both we actually look at our servers on an annual basis we evaluate both ODMs that are in white boxes as well as your typical OEMs and then we're looking to understand the transaction rates and the performance of those particular pieces of hardware we do a price performance evaluation and we sort of upgrade and continue to migrate the farm forward and how about the storage and you buying big giant containers or not as big sands we're not so its commodity storage it's chemist or horizontally scaled across the service we don't believe in centralized storage model no fiber channel no InfiniBand no fiber to know and your stack is your stack our stack is on you've written your own stack to do replication and data migration and run app shots the replication side is actually using my sequel binlog replication okay the backup itself is actually using some open source tools as well as some technologies you stuck on top of it we actually call it sm vault for servers no vault and we've actually developed both a hybrid of open source and our own technologies to make that work do you use tape we do not use tape no tape no euro tape yeah i think frankly i'm not surprised Frank salute with the kind of it yeah and what about the networking what's the strategy there yeah from the networking point of view we use commodity here as well from you know the big two vendors out there cisco and juniper we're continually looking to upgrade we're continually looking to drive layer through technologies down close to the user and have a very reliable very done system let me give you an example in every data center cage location we have at least three tier one providers we have a fully read on the network all the way from the internet through the firewalls through the little answers all the way down to the servers in the rack and we just believe a high-availability enterprise-grade top the bottom and and what about this notion of converged infrastructure you're seeing that a lot is that's something that you're you're looking at you're staying away from you're adopting or we actually think it makes a lot of sense you know I'm not going to tell you we're doing it right now because it's it's pretty bleeding edge and we want to be highly available for the enterprise but this idea of a converged network and systems infrastructure that works together with automation again it's just part of our platform part of our DNA so kind of a single throat to choke and yeah reduce passed me at Pat patch management just a block of infrastructure that that's sensible for you absolutely i mean from our point of view the ServiceNow cloud platform would be that orchestration and automation this is like filled day for me being able to ask of a practitioner that's that's actually building out a big animatic cloud you know sounds awesome and okay well let's see so we hit on s the end we are you here on all the pieces here i guess i think i'm out i think i think i'm thinking about anytime you want yeah that's fantastic i really appreciate the insights you know cuz you know a lot of the lot of the cloud suppliers don't like to talk about you know the internal plumbing but i think it's important you know your customers want to know i mean at the end of the day you don't build a great you know multi-billion dollar business without understanding how infrastructure works in the architecture of the infrastructure I'm a really strong believer that our applications are driving Enterprise forward and I'd have a hard time talking to the cios I talked to you on a regular basis without convincing them but the infrastructure they are relying on for those applications is as solid as it gets do you see the need I do have another one so do you set the need you know remember the early days we all lose I all thought okay here's here comes you know guys like Amazon its commodity infrastructure software lead that's going to lead into the enterprise you're starting to see that happen now but now Amazon's kind of done a one-eighty that's right they're going highly customized infrastructure there's they won't show us their servers but they'll show us so you know no some odm server that's super dense and they say we blow that away because they control their data centers do you see that type of customization requirement for your servers and for your free for your networking we spend time looking at that as well I won't say perhaps we do it quite in-depth as Amazon don't run quite the same size farm they do but we do look at you know the motherboards and the PCI cards and this the the flash disk that's in there the SSD we spend time understand the bios we spend the time understanding how many ports were going to connect to the top Iraq switch we spend time specking all that I mean we're full heart and enterprise platform and our customers depend on us to do that so we have to we have to do that diligence are you using fun all right we still got time are you using flash how are you using it yeah we are using flash we find that the flash arrays we use fusion-io and for those s SD cards we put them into our higher-end database servers from moving actually off spinning media onto flash for the entire farm and one of the way we use it is it helps us get I ops out of the database servers and it actually helps in replication because the way replication works is I'm operating data center a I do my transaction in that database I write it out to the flash because the database is in memory I send it over the parasite the parasites gotta read it off disc and rerun that transaction and keep that replication in sync so that I oh actually does help us keep replication going so using percona my sequel or no no okay so do you raising are on my signal okay do you do atomic rights with fusion we are doing some rights for fusion yes yeah okay so you're essentially bypassing the scuzzy stack and writing directly to we have ability to do that with a new fusion on your driver so I'm not sure they're widely deployed it does it have potential absolutely not it's an amazing performance you can go straight from memory straight to SSD just like you're acting a ram chip why wouldn't we want to not only am I limiting the spinning disk I'm eliminating the overhead of the the storage protocol we'd love to be able to do that yes okay that's understanding the life of the flash / David's lawyers article that we covered the other day because I written specifically for flash as opposed to written for disk how about object stores that's something that you you know we generally don't have a ton of object stores that we do but when we do their document types are attachments to an incident their graphics on a particular application they're part of a workflow that pops up or resent something to the customer and if that is sort of documents become heavy transactional types for reads in the database put those on Mongo okay so and you're doing sort of a combination of block and file or it's all blocked it's all block all block okay well file except I guess what you doing in manga course violence or quasi object that's right awesome I'm having a field day I really appreciate all the insights you know it's this is good i'm actually any the second watch this several times i mean i mean the truth is for us it's all about like i said it's all about talking about folks about infrastructure we think the infrastructure is the core foundation for everything we do in the enterprise apps the apps are really what our customers are about letting them be creators and letting them do our applications but let's face it you know we build the cloud and the club's got to be solid to run those apps my last question so you we've been talking about all these cool innovations when do you see these or do you see these seeping into the the enterprise on-premise do you see that as a sort of viable approach for CIOs or or in your view are they just going to sort of outsourced it mostly to the cloud over the next decade I'm pretty clearly biased at the moment but you know I over your application driven we're talking about infrastructure fair enough from the side I mean I think the things that we're doing in the cloud and the infrastructure are sort of leading-edge I do you think the enterprises are going to adopt that but I'll be honest you there are certain enterprises are ahead of us right there are certain folks that are thinking one or two steps ahead of us because rat just a bigger scale than we are almost though yeah not most but there are some we've learned from them in their banks and yeah i'm thinking the big banks the big big financial institutions we spend time with them learning what they're doing inside so we can actually make the cloud better and they're sharing with you okay absolutely because they're trying to learn too yeah they're ready one happens to somebody that's running on bailing wire right yeah that's amazing innovations actually going on in financial services and it's like the the downturn ever happened yeah well thanks very much for five years all right great stuff keep it right there buddy Jeff Rick and I'll be right back we're live from 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