from San Mateo its the cube covering scaler innovation day brought to you by scaler Livan welcome to the special innovation day with the cube here in San Mateo California heart of Silicon Valley John for the cube our next guest as Steve Newman the co-founder scaler congratulations thanks for having us you guys got a great company here Thanks yeah go ahead glad to have you here so tell the story what's the backstory you guys found it interesting pedigree of founders all tech entrepreneurs tech tech savvy tech athletes as we say tell the backstory how'd it all start and had it all come together so I also traced the story back to I was part of the team that built the original Google Docs and a lot of the early people here at scaler either were part of that Google Docs team or you know they're people we met while we were at Google and really scaler is an outgrowth of the it's a solution to problems we were having trying to run that system at Google you know Google Docs of course became part of a whole ecosystem with Google Drive and Google sheets and there's that you know all these applications working together it's a very complicated system and keeping that humming behind the scenes became a very complicated problem well congratulate ago Google Docs is used by a lot of people so been great success scale is different though you guys are taking a different approach than the competition what's unique about it can you share kind of like the history of where it's going and where it came from and where it's going yeah so you know maybe it'd be helpful like just to kind of set the context a little bit to the blackboard yeah so you know I you know I talked about it's kind of probably put a little flesh on what I was saying about you know there's a very complicated system that we're trying to run in the whole Google Drive ecosystem too there are all these trends in the industry nowadays you know the move to the cloud and micro services and kubernetes and serverless and can use deployment is all everything like these are all great innovations makes you know people are building more complex applications they're evolving faster but it's making things a lot more complicated and to make that concrete imagine that you're running an e-commerce site back in the calm web 1.0 era so you're gonna have a web server maybe a patchy you've got a MySQL database behind that with your inventory and your shopping carts you may be an email gateway and some kind of payment gateway and that's about it that's your that's your system each one of these pieces involved you know going to Fry's buying a computer driving it over the data center slotting it into a rack you know a lot of sweat went into every one of those boxes but there's only about four boxes it's your whole system if you wanted to go faster you threw more hardware at it more ram exactly and like and you know not literally through but literally carried you literally brought in more hardware and so you know took a lot of work just to do the you know that simple system fast forward a couple of decades if you're running uh running an e-commerce site today well you know you're certainly not seeing the inside of a data center you know stripe will run the payments for you you know somebody's on will run the database server and say you know like this is much much you know you know one guy can get this going in an afternoon literally but nobody's running this today this is not a competitive operation today if you're an e-commerce today you also have personalization and advertising based on the surf service history or purchase history and you know there's a separate flow for gifts and you know then printing the you know interfacing to your delivery service and and you know you've got 150 blocks on this diagram and maybe your engineering team doesn't have to be so much larger because each one of those box is so much easier to run but it's still a complicated system and trying to actually understand what's working what's not working why isn't it working and and tracking that down and fixing it this is the challenge day and this and this is where we come in and that's the main focus for today is that you can figure it out but the complexity of the moving parts is the problem exactly so you know and so you see oh you know 10% of the time that somebody comes in to open their shopping cart it fails well you know the problem pops out here but the the root cause turns out to be a problem with your database system back here and and figuring that out you know that's that's the challenge okay so with cloud technology economics has changed how is cloud changing the game so it's interesting you know changes changes the game for our customers and it changes the game for us so for a customer you know kind of we touched on this a little bit like things are a lot easier people run stuff for you you know you're not running your own hardware you're not you know you're often you're not even running your own software you're just consuming a service it's a lot easier to scale up and down so you can do much more ambitious things and you can move a lot faster but you have these complexity problems for us what it presents an an economy of scale opportunity so to you know we step in to help you on the telemetry side what's happening in my system why is it happening when did it start happening what's causing it to happen that all takes a lot of data log data other kinds of data so every one of those components is generating data and by the way for our customers know that they're running a hundred and 50 services instead of four they are generating a lot more data and so traditionally if you're trying to manage that yourself running your own log management cluster or whatever solution you know it's a real challenge to you as you scale up as your system gets more complex you've got so much data to manage we've taken an approach where we're able to service all of our customers out of a single centralized cluster meaning we get an economy of scale each one of our customers gets to work with a basically log management engine that's to scale to our scale rather than the individual customers scale so the older versions of log management had the same kind of complexity challenges you just drew a lot ecommerce as the data types increase so does their complexity is that so the complexity increases and but you also get into just a data scale problem you know suddenly you're generating terabytes of data but you don't you know the you only want to devote a certain budget to the computing resources that are gonna process that data because we can share our processing across all of our customers we we fundamentally changed economics it's a little bit like when you go and run a search and Google thousands literally thousands of servers in that tenth of a second that Google is processing the query 3,000 servers on the Google site may have been involved those aren't your 3,000 servers you know you're sharing those with you know 50 million other people in your data center region but but for a millisecond there those 3,000 servers are all for you and that's that's a big part of how Google is able to give such amazing results so quickly but in still economically yeah economically for them and that's basically on a smaller scale that's what we're doing is you know taking the same hardware and making it all of it available to all of the customers people talk about metrics as the solution to scaling problems is that correct so this is a really interesting question so you know metrics are great you know basically the you know if you look up the definition of a metric it's basically just a measurement on number and you know and it's a great way to boil down you know so I've had 83 million people visit my website today and they did 163 million things in this add mirror and that's you can't make sense of that you can boil it down to you know this is the amount of traffic on the site this was the error rate this was the average response time so these you know these are great it's a great summarization to give you an overall flavor of what's going on the challenge with metrics is that they tend to measure they can be a great way to measure your problems your symptoms sites up it's down it's fast its slow when you want to get to then to the cause of that problem all right exactly why is the site now and I know something's wrong with the database but what's the error message and what you know what's the exact detail here and a metric isn't going to give that to you and in particular when people talk about metrics they tend to have in mind a specific approach to metrics where this flood of events and data very early is distilled down let's count the number of requests measure the average time and then throw away the data and keep the metric that's efficient you know throwing away data means you don't have to pay to manage the data and it gives you this summary but then as soon as you want to drill down you don't have any more data so if you want to look at a different metric one that you didn't set up in advance you can't do it and if you need to go into the the details you can't do an interesting story about that you know when you were at Google you mentioned you the problem statements came from Google but one of things I love about Google is they really kind of nailed the sre model and they clearly decoupled roles you know developers and site reliability engineers who are essentially one-to-many relationship with all the massive hardware and that's a nice operating model it's had a lot of efficiencies was tied together but you guys are kind of saying in a way that does developers use the cloud they become their own sres in a way because this cloud can give them that kind of Google like scale and in smaller ways not like Google size but but that's similar dynamic where there's a lot of compute and a lot of things happening on behalf of the application or the engineers developer as developers become the operator through their role what challenges do they have and what do you see that happening because that's interesting trim because as applications become larger cloud can service them at scale they then become their own sres what yeah well how does that roll out most how do you see that yes I mean and so this is something we see happening at more and more of our customers and one of the implications of that is you have all these people these developers who are now responsible for operations but but they're not special you know they're not that specialist SRE team they're specialists in developing code not in operations they're you know they they minor in operations and and they don't think of it as their real job you know that's the distraction something goes wrong all right they're they're called upon to help fix it they want to get it done as quickly as possible so they can get back to their real job so they're not gonna make the same mental investment in becoming an expert at operations and an expert at the operations tools and the telemetry tools you know they're not gonna be a log management expert on metrics expert um and so they need they need tools that have a gentle learning Kurt have a gentle learning curve and are gonna make it easy for them to get Ian's not really know what they're doing on this side of things but find an answer solve the problem and get back out and that's kind of a concept you guys have of speed to truth exactly so and we mean a couple of things by that sort of most literally we our tool is it's a high performance solution you you hand us your terabytes of log data you ask some question you know what's the trend on this error in this service over the last day and we you know we give you a quick answer Big Data scan through a give you a quick answer but really it's you know that's just part of the overall chain of events which goes from the you know the developer with a problem until they have a solution so they they have to figure out even how to approach the problem what question to ask us you know they have to pose the query and in our interface and so we've done a lot of work to to simplify that learning curve where instead of a complicated query language you can click a button get a graph and then start breaking down that just visually break that down which okay here's the error rate but how does that break down by server or user or whatever dimension and be able to drill down and explore in a you know very kind of straightforward way how would you describe the culture at scaler I mean you guys been around for a while you still growing fast growing startup you haven't done the B round yet got any you guys self-funded it got customers early they pushed you again now 300 plus customers what's the culture like here so you know it's been this has been a fun company to build in part because you know we're into you know the the heart of this company is the engineering team our customers our engineers so you know we're kind of the kind of the same group and that keeps the you know it kind of keeps the inside in the outside very close together and I think that's been a part of the culture we've built is you know we all know why we're building this what it's for you know we use scalar extensively internally but you but even you know even if we weren't we're it's the kind of thing we've used in the past and we're gonna use in the future and so you know I think people are really excited here because you know we understand why and you have an opinion of the future on how it should roll out what's the big problem statement you guys are solving as a company what's it how would you boil that down if asked so by a customer and engineer out there what real problem are you solving that's core problem big problem that's gonna be helping me you know at the end of the day it's giving people the confidence to keep you know building these kind of complicated systems and move quickly because because and this is the business pressure everyone is under you know whatever business you're in it has a digital element and your competitors are in the same you know doing the same thing and they are building these sophisticated systems and they're adding functionality and they're moving quickly you need to be able to do the same thing but it's easy then to get tangled up in this complexity so at the end of the day you know we're giving people the ability to understand those systems and and and the functionality and the software's getting stronger and stronger more complicated with service meshes and micro services as applications start to have these the ability to stand up and tear down services on the fly that's so annoying and they'll even wield more data exact you get more data it gets more complicated actually if you don't mind there's a little story I'd like to tell so hold on just will I clear this out this is going back back to Google and again you know kind of part of the inspiration of you know how he came to build scalar and this doesn't be a story of frustration of you know probably get ourselves into that operation and motivation yep so we were we were working on this project it was building a file system that could tie together Google Docs Google sheets Google Drive Google photos and the black diagram looks kind of like the thing I just erased but there was one particular problem we had that took us months and literally months and months and months to track down you know you'd like to solve a problem in a few minutes or a few hours but this one took months and it had to do with the the indexing system so you have all these files in Google Drive you wanna be able to search and so we had modeled out how we were gonna build this or this search engine you'd think you know Google searches a solve problem but actually so Google web search is four things the whole world can see there's also like Gmail search which is four things that only one person can see so it's lots of separate little indexes those are both solve problems at Google Google Drive is for things a few people can see you share it with your coworker or your whoever and it's actually a very different problem and but we looked at the statistics and we found that the average document our average file was shared with about 1.1 people in other words things were mostly private or maybe you share with one or two people so we said we're just gonna make if something's shared to three people we're just gonna make three copies of it and then now we have just the Gmail problem each copy is for one person and we did the math on how how much work is this going to be to build these indexes and in round numbers we were looking at something like at the time this would be so much larger now but at the time we had maybe one billion documents and files in the system each one was shared to about 1.1 people maybe it was a thousand words long on average and maybe it would change be edited once per day on average so we had about a trillion word updates per day if you multiply all that together and so we allocate it we put in a request and purchase machines to handle that much traffic and we started bringing up the system and immediately collapsed it was completely overloaded and we checked our numbers and we check them again yeah 1.1 about a billion whatever and but then work into the system with just way beyond them and we looked at our metrics so you know measuring the number documents measuring each of these things all the metrics looked right to make a month's long story short these metrics and averages were hiding some funny business there turned out there was this type of use case read of occasional documents that were shared to thousands of people and one of there was a specific example it was the signup sheet for the Google company picnic this is a spreadsheet it was shared to about 5,000 people so it wasn't the whole company but you know a big chunk of Mountain View which meant it was I don't know let's say 20 thousand words long because it had you know the name and a couple other things for each person this is one document but shared to 5,000 people and you know during the period people were signing up maybe it was changing a couple thousand times per day so you multiply out just this document and you get 200 billion word updates for that one document in a day where we're estimating a trillion for the whole earth and so there was something like a hundred documents in this kid Google was hamstringing your own thing we were hamstrung our own thing there were about a hundred examples like this so now we're up to 20 trillion and like that was the whole problem these hundred files and we would have never found that until we got way down into the details of the the logs which in this two months just took month so because we didn't have the tools because we didn't have scaler yeah and I think this is the kind of anomaly you might see with Web Services evolving with micro services which someone has an API interface with some other SAS as apps start to rely on each other this is a new dynamic we're seeing as SLA s are also tied together so the question is whose fault is it exactly you have to whose fault is it and also things get so much more varied now you know again web 1.0 e-commerce you buy a thing you buy a thing that's all the same now you're building a social media site or whatever you've got 8 followers you've got 8 million followers this person has three movies rented on Netflix this person has three thousand movies everything's different and so then you get these funny things hiding yeah you're flying blind if you don't get all the data exposed it's like it's like you know blind person trying to read Braille as we heard earlier see if thanks so much for sharing the insight great story I'm John furry you're here for the q4 innovation day at scalers headquarters thanks for watching

>> from San Matteo. It's the Cube covering scaler. Innovation Day Brought to You by scaler. >> Welcome to this Special Cube Innovation Day. Here in San Mateo, California Scale is headquarters for a coast of the Cube. We're here with two great guests. Claudia Carpenter co founder Andy McAlister, Who's Dev evangelist? Uh, great to have you guys here a chat before we came on. Thanks for having us >> Great to be >> so scaler. It's all about the logs. The answer is in the logs. That's the title of the segment Them. I'll see the log files with a lot of exhaust in their data value extracting that, but it's got more operational impact. What's what's the Why is the answer in the locks? >> Because that's where the real information is. It's one thing to be able to tell that something is going around when your systems, but what is going wrong as engineers, what we tend to do is the old print. If it's like here's everything I can think of in this moment and leave it as breadcrumbs for myself to find later, then I need to go and look at those bread crumbs >> in a challenge. Of course, with this is that logs themselves are proliferating. There's lots of data. There's lots of services inside this logs, so you've gotta be able to find your answers as fast as possible. You can't afford Teo. Wait for something else. T lead you to them. You need to deep dive >> the way you guys have this saying it's the place to start. What does that mean? Why? Why is that the new approach? >> What We're trying to differentiate because there's this trend right now in the Dev Ops world towards metrics because they're much smaller to store it, pre digesting what's going on in your systems. And then you just play a lot of graphs and things like that. We agree with that. You do need to be able to see what's going on. You need to be able to set alerts. Metrics are good, but they only get you so far. A lot of people will go through. Look at metrics, dig through and then they stop, switch over and go to their logs. We like to start with the logs, build our metrics from them, and then we go direct to >> the source. I think a minute explain what you mean by metrics, because that has multiple meanings. Because the current way around metrics and you kind of talked about a new approach. Could you just take a minute? Explain what you meant by metrics and how logs are setting up the measures. The difference there. >> So to me, metrics is just counting things right? So at log files of these long textual representations of what's going on in my system and it's impossible to visually parce that I mean literally 10,000 lines. So you count. I've got five of this one in six of this one, and it's much smaller to store. I've got five of this one and six of this one, but that's also not very much information, so that's really the difference. >> But, you know, we have customers who use their metrics to help them indicate something might be wrong inside of here. The problem is, is that modern environments where we have instant gratification, needs and people you know, we'd be wait five seconds. Basically, it's a law sale online here. You need to know what's went wrong, not just where we went wrong or that something went wrong. So building for the logs to the metrics allows you to also have a perfect time back to that specific entrance ancient entrance that lets you be you out. What was wrong? >> He mention Claudia Death ops. And this is really kind of think of fun market because Dev Ops is now going mainstream and see the enterprise now started to adopt. It's still Jean Kim from Enterprise. Debs estimates only 3% of enterprise really there yet. So the action's on the cloud Native Public Cloud side where it's, you know, full blown, you know, cloud native more services. They're coming to see Cooper Netease things of that nature out there. And these services are being stood up and torn down while the rhythmically like. So with who the hell stores that data? That's the logs. The nature of log files and data is changing radically with Dev ops. I'm certainly this is going to be more complications but developers and figuring out what's what. How do you see that? What's your reaction to that trend? >> Yeah, so Dev Ops is a very exciting thing. At were Google. It was sort of like the new thing is the developers had to do their own operations, and that's where this comes from. Unfortunately, a lot of enterprise will just rename their ops people devil apps, and that's not the same thing. It's literally developers doing operations, Um, and right now that it's never been so exciting as as it is right now in the text axe, because you could get so much that's open source. Pre built glue this all these things together. But since you haven't written the code yourself, you've no way deal which going on. So it's kind of like Braille. You've got to go back and look and feel your way through it to figure out what's going on. And that's where logs come into play. >> The logs essentially, you know, lift up, get people eyesight into visibility of things that they care about. Absolute. So what's this red thing? Somebody read what is written? Rennes. >> One of the approaches. You'll hear things like golden signals. You'll hear youse, and you'll hear a red Corvette stands for rates, a rose and duration. And ready is a concept that says, How do you actually work with some of these complex technologies working with you're talking about and actually determined where your problems are. So if you think about it, rate is kind of how much traffic's going through a signal for this as a metric, it's accumulative number. So to back to Claudia's point, it's just number here. But if you're trapping goes up, you want to know what's going wrong here is self explanatory. Something broke, fix it, and then duration is how long things took. You talked about communities, Communities works hands in hands with this concept of micro services. Micro services are everywhere, and there were Khun B places that have thousands of little services, all serving the bigger need here. If one of them goes slow, you need to know what went slow as fast as possible. So rate duration and air is actually combined to give you the overall health of your system. While at the same point logs elect, you figure out what was causing >> the problem we'll take. I'm intrigued by what Claudia said. They're on this. You know, Braille concept is essentially a lot of people are flying blind date with what's going on, but you mentioned micro services. That's one area that's coming. Got state full data. Stateless data. They were given a P I economy. Certainly a state becomes important for these applications. You know, the developers don't may or may not know what's happening, so they need to have some intelligence. Also, security we've seen in the cloud. When you have a lot of people standing up instances whether it's on Amazon or other clouds, they don't actually have security on some of their things. So they got it. Figure out the trails of what the data looks like they need the log files to have understanding of. Did something happened? What happened? Why? What is the bottom line here? Claudia? What what people do to kind of get visibility So they're not flying blind as developers and organizations. >> Well, you gotta log everything you can within reason. They always have to take into account privacy and security. But logs much as you can and pull logs from every one of the components in your systems. The micro services that day was just talking about are so cool. And as engineers, we can't resist them way. Love, complexity >> and cool things. >> Things especially cool things and new things. >> New >> green things. Sorry, easily distracted. But there they are, harder to support. They can be a really difficult environment. So again it's back to bread crumbs, leaving that that trail and being able to go back and reconstruct what happened. >> Okay, what's the coolest thing about scaler since we thought about cool and relevant? You guys certainly in the relevant side thing. Check the box there. What's cool? What's cool about scaler telling us? >> That's great. Answer What isn't. But you know, honestly, when I came to work here, I no idea I was familiar with Log Management was really with long search and so forth. And the first time I actually saw the product, my jaw dropped. Okay, I now go to a trade show, for instance, and I'm showing people to use this. And I hit my return button to get my results. And you showed band with can be really bad and it stalls for 1/10 of a second, and I complain about it now. No, there is nothing quite as thrilling as getting your results as fast as you can think about them. Almost your thought processes the slow part of determining what's going on, and that is mind boggling. >> So the speed is the killer. >> The speed is like what killed me. But honestly, something that Chloe's been heavily involved in It takes you two minutes to get started. I mean, there's no long learning curve there. You get the product and you are there. You're ready to go >> close about ease of use and simplicity, because developers are fickle, but they're also loyal. Do you have a good product? They loved to get in that love the freebie. You know, the 30 day trial, They'll they'll kick the tires on anything. But the product isn't working. You hear about it when it does work. This mass traffic to people you know pound at the doorstep of the product. What's the compelling value proposition for the developer out there? Because they >> don't want to >> waste time. That's like the killer death to any product for development. Waste their time. They don't want to deal with it. >> So we live in the TL D our world right now. Frankly, if I have to read something, I usually move on on DH. That's the approach we take with scaler as well. Yes, we have some documentation, but I always feel like I have failed with the user interface design. If I require you to go read the documentation. So I try to take that into account with everything that we that we put out there making it really easy and fast it just jumping in, try stuff. >> How do you get to solve the complex complexity problem through attraction software? What's the secret sauce for the simplicity of this system? >> For me, it's a complete lack of patients. It's just like I wouldn't put up with that. I'm not gonna ask you to. Frankly, I view this sounds a little bit trite, but I've you Software's a relationship, and I view whoever is looking at it as a peer of mine, and I would be embarrassed if they couldn't figure it out if it wasn't obvious. But it is. We do have this sort of slope here of people who really know what's going on and people wanna optimize. This is your 80 20 split on people that don't know what just want to come in. I want both of them to be happy, so we need to blend those >> to talk about the value proposition of what you guys have because we've been covering you know log file mentioned Lock Management's Splunk events. We've gone, too. There's been no solution that I think may be going on 10 years old, that were once cutting edge. But the world changes so fast with Amazon Web services with Google Cloud with azure. Then get the international clouds out there as well. It's it's here. I mean, the scale is there, you got compute. You got the edge of the network right around the corner in the data problem's not going away. Log files going be needed. You have all this data exhausted, these value. >> If anything, there's always going to be more data that's out there. You're going to have more sources of that data coming in here. You're talking a little bit about you have the hybrid cloud. Where's part on prom? Part in the cloud. You could have multi clouds where across his boundaries. You're gonna have the wonderful coyote world where you have no idea when or where you're going to get an upload from too. This too and EJ environment. And you've got to worry about those and at the same time time, the logging, everything, the breadcrumbs. You have ephemeral events. They're not always there, and those are the ones that kill you. So the model is really simple and applaud Claudia for conning concept wise. But you're playing with concept of kiss, right? We'll hear its keep it simple and sophisticated at the same time. So I can teach you to do this demo in two minutes flat, and from there you can teach yourself everything else that this product's capable of doing it. That simple >> talk about who? The person out there that you want to use his product and why should they give scale or look what's in it for them. >> So for me, I think the perfect is to have Dev ops use it. It's developers. We really have designed a product less for ops and more for engineers. So one of the things that is different about scaler is you have somebody come in and set it up, parsed logs that ingestion of logs, which is different than splunk and sumo on DH. Then it's ready to use right out of the box. So for me, I think that our sweet spot, his engineers, because a lot of our formulations of things you do are more technical you're thinking about about you know what air the patterns here. I'm not going to say it's calculus, because then that wouldn't be simple. But it's along. Those >> engineers might be can also cloud Native is a really key party. People who were cloud native. We're actually looking at four in the cloud or cloud migration, >> right way C a lot. For instance, in the Croup. In any space from the Cloud Native Compute Foundation, we're seeing a tremendous instrument interest in Prometheus. We're seeing a lot of interest in usto with service mesh. The nice thing is that they are already all admitting logs themselves. And so, from our viewpoint, we bring them in. We put them together. So now you can look at each piece as it relates to the very other piece >> Claudia share with the folks who, watching this just some anecdotal use cases of what you guys have used internally, whether customers that give him a feel for how awesome scaler is and what's the what could they expect? >> Well, put me on the spot here. Um, >> I'll kick off. So we have a customer in Germany there need commerce shop, They have 1,000 engineers for here. When we started the product we replace because it was on a charge basis that was basically per user. They came back and they said, Oh my God, you don't understand our queries Air taking 15 minutes to get back By the time the quarry comes back, the engineer's forgotten why he asked the question for this. And so they loaded up. They rapidly discovered something unique. It's that they can discover things because anyone can use it. We now have 500 engineers that touch the log files every day, I will attest. Having written code myself, nobody reads log files for fun. But Scaler makes it easy to discover new things and new connections. And they actually look at what house >> discoveries of real value, proper >> discovery is a massive value proposition. Uh, where you figure out things that you don't know about back to that events thing that Claudia started about was, you can only measure the events that you can already considered. You can't measure things that didn't happen >> close. It quickly thought what the culture on David could chime in. What's the culture like here scaler? >> It is a unique culture and I know everyone probably says that about their startup, but we keep work life balance as a very important component. We're such nerds and unabashedly nerds. Wait, what we do. It's a joyful atmosphere to work in. Our founder, Steve Newman, is there in his flat, his flannel shirt, his socks cruising around. Um, and we are very much into our quality barcode. We have a lot of the principles of Google sort of combined into a start up. I mean to say it's a very honest environment, >> Sol. Heart problems make it a good environment. >> Yeah, and I value provide real values, are critical >> for me and have fun at the same point in time. The people here work hard, but they share what they're working on. They share information. They're not afraid to answer the what are you working on? Question. But we always managed to have fun. We are a pretty tight group that way. >> Well, thanks for sharing that insight. We have a lot of fun here in Innovation Day with the Q p. I'm John Furia. Thanks for watching

live from Las Vegas it's the cube covering AWS reinvent 2018 brought to you by Amazon Web Services Intel and their ecosystem partners welcome back everyone live here the cube coverage at Amazon Web service AWS reinvent 2018 our sixth year covering Amazon now 52,000 lost people here packed house this is where the industry gathers to really kind of check out the future where the state of the cloud business is what it means to enterprise I'm John Fourier the post of the cube with Lauren Cooney co-host me.we this week on set one of two sets here our next two guests Jeff monk resulting systems engineer stealthWatch cloud that's now part of Cisco Systems and Earth has been Product Marketing Manager jetbrains welcome to the cube guys thanks for coming on thanks launched six years now we've been covering Amazon we were here when kind of people didn't really understand what it was we saw here so Jerry Chen just gave him a venture capitalist and Braille app and we're like this is gonna be big it's big but the big news here this week is on premises okay you guys cisco you own premises with routing networking developers of programming applications in the cloud needs to run on premise it's a big theme it's all kind of coming together it's kind of first validation this year that on-premises is not going away and cloud is becoming more prevalent for data and analytics for coding for DevOps but now working seamlessly together you guys agree with this recently announced the deal with AWS right you have networking which the critical part of the holy trinity of infrastructure network storage compute powering a new class of software development and tools what's your view on this I mean give us a take yeah so from a Cisco stealthWatch standpoint like you said we see that customers are not necessarily going away from on-premise deployments a lot of organizations have got large data centers and Colo facilities they still run all right and they've also got workloads in the public cloud so what we see is you know any some kind of mixture of organizations that have still got bare metal servers and virtual machines on premise that they need visibility into and one protect then they've also got public cloud workloads that are virtual machines but then they've gone beyond virtual machines and there are things like micro services and server lists and containers and they need a solution that can protect all those different environments and that's what stealthWatch comes into play and i want to get you guys saw it on on this because i'll see now security used to be a blocker for cloud it can't put seven the cloud skids not secure now security is their baseline at least needs more work you've got to have that visibility and you guys have a programmable strategy for the network is now coding be pcs is becoming more important than ever before right how is security evolving as compute start to get more powerful storage of storage data it's not going away it's only growing with IOT and IOT edge with connectivity networking now has to up its game write an application of elves don't want anything to do with all that anymore they want to just program so what's this mean for people what are security right for security yeah so what we're seeing and I mentioned a second ago was the expansion into micro services serverless cloud native if you will and organizations are continuing to go that route but what they don't realize is as they expand into those different technologies they're actually increased creating an increasing attack surface if you will right they're not really thinking about that and what they're doing is opening up multiple new points out to the internet that are vulnerable and it to exposure and risk right so they're not thinking about securing those new environments that are deploying and that's where we come into play also awesome let's talk about jet Breen what do you guys do what's the relationship with Cisco how do you fit in what's the story so let me start with introducing jetbrains little but you're just talking about all these various spaces where people have to run their code nowadays yeah if you want to develop for all these environments you need tools that allow you to develop for all these environments at JetBrains that were tooling professionals what we do we are software developers we make tools for software developers we really want to give the developer all this power in their hands to be able to develop insight for example containers and step through their code as they go inside these environments of course our own products and our own services they are all a lot of them are hosts on AWS and Cisco comes in there and healthy let's make sure that all of our servants that we have online remains secure and the relationship with Cisco is part of the go-to-market you guys share products together what's the relationship as jetbrains is actually a stealthWatch customer they've been a customer for a few years now and we actually protect all of their Amazon workloads they've got deployed in the Amazon infrastructure anything from ec2 instances to RDS redshift lambdas pretty much any sort of service that they're using from a compute standpoint in Amazon stealthWatch cause in protecting for a few years now so with kubernetes and now lambda the old days was was still grade you spit up an instance ten seconds lambda you can do this in really really high velocity how does that change the tooling how does it impact your world it's a customer so for us as the customer self watch it impacts us that we have to of course make sure that whenever these lambdas fire we know what's going on and we can see what's happening and one of the things we really want to do within Jefferson we want to give our developers we want to empower they want to make sure that they can experiment that they can make new things and it's all Excel what really helps us make sure that when our developers are out there doing things we can still maintain that we're following the best practices and everything stay secure how does automation guys weave in because kubernetes is a big battleground right now we're seeing important one as orchestrating and managing cluster certainly the state of application data unstated applications also with AP is obviously growing visibility is critical but automations may be right around the horizon ku Bernays at some point gonna be automated away and if so what's that looked like from software standpoint because yeah it's dynamic now so what we see from a kubernetes and a container orchestration perspective is that the kubernetes itself is designed to do the automation all right it's elastic expand and contract right but what you may be looking at today is a small kubernetes cluster with a couple of nodes and a couple dozen pods then all sudden tomorrow based on load you could be looking at hundreds of nodes and thousands of pots a massively increased attack surface if you will it right there's a building into and trying to figure out what's going on there right stealth watts cloud luckily we're there we're in kubernetes today and what we do is we deploy automatically in the kubernetes environment and in a way that allows us to expand with you automatically so as your cluster expands we will give you complete visibility into everything that's moving east west in kubernetes as well as north south so it's a very simple deployment doesn't matter where kubernetes lives we've got you covered if people are going to download stealthWatch from the catalog right what is it how would you describe right so stealthWatch cloud it is a SAS offering all right so we get asked that a lot just today over in the booth you know we've got a lot of questions about where do we put our sensors where do you put the collectors people if they're having a hard time wrapping their heads around the fact that it's straight API calls okay we're bringing in cloud trail we're bringing in I am and cloud watch BPC flow logs right and we're bringing it all in all automated over the API AWS - AWS where we live and it is a SAS billing offering writes if there's nothing that you have to go deploy it's a 5-minute integration you can buy it right there on the AWS marketplace like you said for public or private network monitoring and it's a subscription billing so it's a true SAS you're looking to kind of expand you know your footprint in this space with kubernetes is there any thought of you know some sort of code donation to kubernetes to actually increase your footprint among users and get them more engaged or is that something that you you know talked about thought about things like that donating code donating some code yeah I don't honestly don't think there's anything that we've ever discussed about donating commenting like that what about you guys are donating code to the kubernetes project well just to increase your footprint right so you would have available as a component of kubernetes and people would put into there great idea yeah yeah it's not something that I know that we discussed but yeah I mean if we could deploy something that would be open source that we actually part of that project that would be a huge visibility for us and I think that's big sensitive you look at what's going on in Cisco whether things like to give you guys a prop here is that the def net developer community has really taken - cloud native and with definite create dev net at Cisco live and Cisco Barcelona we've been this past year what a sea change I mean you got command line interface dudes going hey I need to be dashboard oriented meaning I gotta automate stuff so the notion of programming the network it's not a foreign concept to network engineers they're pretty smart right they get things so how is this world of all I mean how is the persona of a Cisco customer that needs to get more software development shops going what's it like I mean is there future dashboards as their future gonna be scripts event alerts let me manage it so how do you guys see that persona evolving I think what we see and you can probably relate to this also erst is that more and more organizations it doesn't matter how averse they are to cloud and new development technologies more organizations are going towards a DevOps oh yeah framework with C ICD constant continuous integration and continuous delivery right so it's hard to avoid the fact that that's where the paradigm is shifting and in doing so as we move into more cloud native and serverless capabilities you're looking at things that don't get necessarily involved operating systems and IP addresses and traditional endpoints and that's where most organizations are going so and so from a security perspective we've got to go there also know about your relationship with just as a customer are you happy what's it like how's the product so if I were very happy we've had some great experiences with the onboarding of stealthWatch cloud yeah we had some of course you know as you're starting to get started we needed a little bit of assistance getting used to the tool and getting started and getting anything configured the support was very helpful and they really helped us get started and then at some point we actually did some of this cloud automation and we set up terraform scripts so we could actually automatically configure stealthWatch cloud into many of our AWS accounts great great stuff final question for Cisco what's next for you guys on the product side anything going on give a quick plug of what's happened yeah I'd say what's next for us from a stealth watch cloud standpoint is you're going to see more integration with the Cisco portfolio we're integrating with the Cisco identity services engine integrating with the next-gen firewall integrating with the new encrypted traffic analytics that you've probably discussed here on the cube before so it's a tiger portfolio integration because that really sets us apart awesome guys thanks for coming on the key appreciate the insight good to see a customer here thanks for coming I appreciate very good job kubernetes at the head start as at the center of all the action with developers cluster man has been scaling up lamda server list this is the really the fasting programming gold networks is key the queue bringing all the coverage here live in Las Vegas for 80 bus reinvent 2018 I'm Shepard Lauren Cooney stay with us for more coverage after this short break [Music]

[Music] from San Francisco it's the covering Red Hat summit 2018 brought to you by Red Hat everyone welcome back is the cubes live coverage here in San Francisco Red Hat summit 2018 I'm Sean furry co-host of the cube with my coasts analyst this week John Troyer who's the co-founder of tech reckoning advisory and Community Development firm our next guess is red hash Balakrishnan is the general manager of OpenStack for Red Hat welcome to the cube good to see you ready to be here so OpenStack is very hot obviously with the with the with the trends we've been covering from day one been phenomenal to watch that grow and change but with kubernetes you seeing cloud native to robust communities you got application developers and you got under the hood infrastructure so congratulations and you know what's what's the impact of that what is how is OpenStack impacted by the cloud native trend and what is Red Hat doing they're the best epidermis ation of that is openshift on OpenStack if you had caught the keynotes earlier today there was a demo that we did whereby they were spawning open shifts on bare metal using OpenStack and then you run open shift on power that's what we kind of see as the normed implementation for customers looking to get - I want an open infrastructure on Prem which is OpenStack and then eventually want to get to a multi cloud application platform on top of it that makes up the hybrid cloud right so it's a essential ingredient to the hybrid cloud that customers that are trying to get to and open shifts role in this is what I'm assuming we are asked about openshift ownerships will be multi cloud from a application platform perspective right so OpenStack is all about the infrastructure so as long as you're worrying about info or deployment management lifecycle that's going to be openstax remet once you're thinking about applications themselves the packaging of it the delivery of it and the lifecycle of it then you're in openshift land so how do you bring both these things together in a way that is easier simpler and long-standing is the opportunity and the challenge in front of us so the good news is customers are already taking us there and there's a lot of production workflow is happening on OpenStack but I got to ask the question that someone might ask who hasn't been paying attention in a year or so it was thick hey OpenStack good remember that was what's new with OpenStack what would you say that person if they asked you that question about what's new with OpenStack the answer would be something along the lines of boring is the new normal right we have taken the excitement out of OpenStack you know the conversations are on containers so OpenStack has now become the open infrastructure that customers can bring in with confidence right so that's kind of the boring Linux story but you know what that's what we thrive on right our job as reddit is to make sure that we take away the complexities involved in open source innovation and make it easy for production deployment right so that's what we're doing with OpenStack too and I'm glad that in five years we've been able to get here I definitely I think along with boring gos clarity right last year the cube was that OpenStack summit will be there again in two weeks so with you and I enjoy seeing you again for it the last year there was a lot of you know containers versus there was some confusion like where people got sorted out in their head oh this is the infrastructure layer and then this is the a play I think now people have gotten it sorted out in their head open open shipped on OpenStack very clear message so a meaning of the community in two weeks in any comments on the growth of the open OpenStack community the end users that are there the the depth of experience it seemed like last year was great everywhere for OpenStack on the edge it ended you know set top devices and pull top devices all the way to OpenStack in in private data centers and and for various security or logistical reasons where is OpenStack today yeah I think that he phrased would be workload optimization so OpenStack has now evolved to become optimized for various workloads so NFV was a workload that people were talking about now people are in when customers are in production across the globe you know beat Verizon or the some of the largest telcos that we have in any and a pack as well the fact that you can actually transform the network using OpenStack has become real today now the conversation is going from core of the data center to the edge which is radio networks so the fact that you can have a unified fabric which can transcend from data center all the way to a radio and that can be OpenStack is a you know great testament to the fact that a community has rallied around OpenStack and you know delivering on features that customers are demanding pouring is the new normal of that is boring implies reliable no-drama clean you know working if you had to kind of put a priority in a list of the top things just that it are still being worked on I see the job is never done with infrastructure always evolving about DevOps certainly shows that with programmability what are the key areas still on the table for OpenStack that are that are key discussion points where there's still innovation to be done and built upon I think the first one is it's like going from a car to a self-driving car how can we get that infrastructure to autonomously manage itself we were talking about network earlier even in that context how do you get to a implementation of OpenStack that can self manage itself so there's a huge opportunity to make sure that the tooling gets richer to be able to not just deploy manage but fine-tune the infrastructure itself as we go along so clearly you know you can call it AI machine learning implementation you on OpenStack to make sure that the benefit is occurring to the administrator that's an opportunity area the second thing is the containers and OpenStack that we taught touched upon earlier OpenShift on OpenStack in many ways is going to be the cookie cutter that we're gonna see everywhere there's going to be private cloud if you've got a private cloud it's gotta be an open shift or on OpenStack and if it's not I would like to know why right it's a it becomes a de-facto standard you start to have and they enablement skills training for a few folks as you talk to the IT consumer right the the IT admins out there you know what's the message in terms of upskilling and managing say an OpenStack installation and and what does Red Hat doing to help them come along yeah so those who are comfortable with Braille Linux skills are able to graduate easily over to OpenStack as well so we've been nationally focused on making sure that we are training the loyal Linux installed based customers and with the addition of the fact that now the learnings offerings that we have are not product specific but more at the level of the individual can get a subscription for all the products that reddit has you could get learning access to learning so that does help make sure that people are able to graduate or evolve from being able to manage Linux to manage a cloud and the and face the brave new world of hybrid cloud that's happening in front of our eyes but let's talk about the customer conversations you're having as the general manager of the stack red hat what what are the what's the nature of the conversations are they talking about high availability performance or is it more under the hood about open shift and containers or they range across the board depending upon the use cases whose they do range but the higher or the bit is that applications is where the focuses well closes where the focus is so the infrastructure in many ways needs to get out of the way to make sure that the applications can be moving from the speed of thought to execution right so that's where the customer conversations are going so which is kind of ties back to the boring is the new normal as well so if we can make sure that OpenStack is boring enough that all the energy is focused on developing applications that are needed for the enterprise then I think the job is done self-driving OpenStack it means when applications are just running and that self-healing concepts you were talking about automation is happening exactly that's the opportunity in front of us so you know it's by N's code by code we will get there I think I love the demo this morning which showed that off right bare metal stacks sitting there on stage from different vendors right actually you're the you know OpenStack is the infrastructure layer so it's it's out there with servers from Dell and HP II and others right and then booting up and then the demo with the with Amadeus showing you know OpenStack and public clouds with openshift all on top also showed how it fit into this whole multi cloud stack is it is it challenging to to be the layer with with the hardware hardware heterogeneous enough at this point that OpenStack can handle it are there any issues they're working with different OEMs and if you look at the history of red add that's what we've done right so the rel became rel because of the fact that we were able to abstract multi various innovation that was happening at the so being able to bring that for OpenStack is like we've got you know that's the right to swipe the you know employee card if you will right so I think the game is going back to what you were only talking about the game is evolving to now that you have the infrastructure which abstracts the compute storage networking etc how do you make sure that the capacity that you've created it's applied to where the need is most right for example if you're a telco and if you're enabling Phi G IOT you want to make sure that the capacity is closest to where the customer fool is right so being able to react to customer needs or you know the customers customers needs around where the capacity has to be for infrastructure is the programmability part that we've you know we can enable right so that's a fascinating place to get into I know you are technology users yourself right so clearly you can relate to the fact that if you can make available just enough technology for the right use case then I think we have a winner at hand yeah and taking as you said taking the complexity out of it also means automating away some of those administrative roles and moving to the operational piece of it which developers want to just run their code on it kind of makes things go a little faster and and so ok so I get that and I but I got to ask the question that's more Redhead specific that you could weigh in on this because this is a real legacy question around red hats business model you guys have been very strong with rel the the the record speaks for itself in terms of warranty and and serviceability you guys give like I mean how many years is it now like a zillion years that support for rel OpenStack is boring is Red Hat bringing that level of support now how many years because if I use it I'm gonna need to have support what's the Red Hat current model on support in terms of versioning xand the things that you guys do with customers thank you for bringing that up what have you been consciously doing is to make sure that we have lifecycle that is meeting two different customers segments that we are talking about one is customers who want to be with the latest and the greatest closer to the trunk so every six months there is an openstack released they want to be close enough they want to be consuming it but it's gotta be production ready in their environment the second set of customers are the ones who are saying hey look the infrastructure part needs to stay there cemented well and then every maybe a couple of years I'll take a real look at you know bringing in the new code to light up additional functionality or on storage or network etc so when you look at both the camps then the need is to have a dual life cycle so what we have done is with OpenStack platform 10 which is two years ago we have a up to five year lifecycle release so obvious that platform 10 was extensible up to five years and then every two releases from there 11 and 12 are for just one year alone and then we come back to again a major release which is OSP 13 which will be another five years I know it can be and they get the full Red Hat support that they're used to that's right so there are years that you're able to either stay at 10 or you could be the one who's going from 10 to 11 to 12 to 13 there are some customers were saying staying at 10 and then I won't go over to 13 and how do you do that we'll be a industry first and that's what we have been addressing from an engineering perspective is differentiated - I think that's a good selling point guy that's always a great thing about Red Hat you guys have good support give the customers confidence or not you guys aren't new to the enterprise and these kinds of customers so right - what are you doing here at the show red hat summit 2018 what's on your agenda what some of the hallway conversations you're hearing customer briefings obviously some of the keynote highlights were pretty impressive what going on for you it's a Volvo OpenShift on OpenStack that's where the current and the future is and it's not something that you have to wait for the reality is that when you're thinking about containers you might be starting very small but the reality is that you're going to have a reasonably sized farm that needs to power all the innovation that's going to happen in your organization so given that you need to have an infrastructure management solution thought through and implemented on day one itself so that's what OpenStack does so when you can roll out OpenStack and then on top of it bring in openshift then you not only have to you're not only taking care of today's needs but also as you scale and back to the point we were talking about moving the capacity where is needed you have a elastic infrastructure that can go where the workload is demanding the most attention so here's another question that might come up from when I asked you and you probably got this but I'll just bring it up anyway I'm a customer of OpenStack or someone kicking the tires learning about deploying up a stack I say ritesh what is all this cloud native stuff I see kubernetes out there what does that mean for me visa V OpenStack and all the efforts going on around kubernetes and above and the application pieces of the stack right let's say if you looked at the rear view mirror five years ago when we looked at cloud native as a contract the tendency was that hey look I need to be developing net new applications that's the only scenario where cloud native would be thought thought off now fast forward five years now what has happened is that cloud native and DevOps culture has become the default if you are a developer if you're not sort of in that ploughed native and DevOps then you are working on yesterday's problem in many ways so if digital transformation is urging organizations to drive - as cloud native applications then cloud native applications require an infrastructure that's fungible inelastic and that's how openshift on OpenStack again coming back to the point of that's the future that customers can build on today and moving forward so summarize I would say what I heard you saying periphery if I'm wrong open ship is a nice bridge layer or an up bridge layer but a connection point if you bet on open ship you're gonna have best of both worlds that that's a good summary and you gotta be you know betting on open first of all is the first order a bet that you should be making once you've bet on open then the question is you gotta bet on an infrastructure choice that's OpenStack and you gotta bet on an application platform choice that's open shift once you've got both of these I think then the question is what are you going to do with your spare time okay count all the cash you're making from all the savings but also choice is key you get all this choice and flexibility is a big upside I would imagine British thanks for coming on sharing your insight on the queue appreciate it thanks for letting us know what's going on and best of luck see you in Vancouver thank you for having okay so the cube live coverage here in San Francisco for Red Hat summit 2018 John four with John Troy you're more coverage after this short break