>> From The Cube Studios in Palo Alto and Boston, bringing you data driven insights from The Cube at ETR. This is "Breaking Analysis" with Dave Vellante. >> The reverse momentum in tech stocks caused by rising interest rates, less attractive discounted cash flow models, and more tepid forward guidance, can be easily measured by public market valuations. And while there's lots of discussion about the impact on private companies and cash runway and 409A valuations, measuring the performance of non-public companies isn't as easy. IPOs have dried up and public statements by private companies, of course, they accentuate the good and they kind of hide the bad. Real data, unless you're an insider, is hard to find. Hello and welcome to this week's "Wikibon Cube Insights" powered by ETR. In this "Breaking Analysis", we unlock some of the secrets that non-public, emerging tech companies may or may not be sharing. And we do this by introducing you to a capability from ETR that we've not exposed you to over the past couple of years, it's called the Emerging Technologies Survey, and it is packed with sentiment data and performance data based on surveys of more than a thousand CIOs and IT buyers covering more than 400 companies. And we've invited back our colleague, Erik Bradley of ETR to help explain the survey and the data that we're going to cover today. Erik, this survey is something that I've not personally spent much time on, but I'm blown away at the data. It's really unique and detailed. First of all, welcome. Good to see you again. >> Great to see you too, Dave, and I'm really happy to be talking about the ETS or the Emerging Technology Survey. Even our own clients of constituents probably don't spend as much time in here as they should. >> Yeah, because there's so much in the mainstream, but let's pull up a slide to bring out the survey composition. Tell us about the study. How often do you run it? What's the background and the methodology? >> Yeah, you were just spot on the way you were talking about the private tech companies out there. So what we did is we decided to take all the vendors that we track that are not yet public and move 'em over to the ETS. And there isn't a lot of information out there. If you're not in Silicon (indistinct), you're not going to get this stuff. So PitchBook and Tech Crunch are two out there that gives some data on these guys. But what we really wanted to do was go out to our community. We have 6,000, ITDMs in our community. We wanted to ask them, "Are you aware of these companies? And if so, are you allocating any resources to them? Are you planning to evaluate them," and really just kind of figure out what we can do. So this particular survey, as you can see, 1000 plus responses, over 450 vendors that we track. And essentially what we're trying to do here is talk about your evaluation and awareness of these companies and also your utilization. And also if you're not utilizing 'em, then we can also figure out your sales conversion or churn. So this is interesting, not only for the ITDMs themselves to figure out what their peers are evaluating and what they should put in POCs against the big guys when contracts come up. But it's also really interesting for the tech vendors themselves to see how they're performing. >> And you can see 2/3 of the respondents are director level of above. You got 28% is C-suite. There is of course a North America bias, 70, 75% is North America. But these smaller companies, you know, that's when they start doing business. So, okay. We're going to do a couple of things here today. First, we're going to give you the big picture across the sectors that ETR covers within the ETS survey. And then we're going to look at the high and low sentiment for the larger private companies. And then we're going to do the same for the smaller private companies, the ones that don't have as much mindshare. And then I'm going to put those two groups together and we're going to look at two dimensions, actually three dimensions, which companies are being evaluated the most. Second, companies are getting the most usage and adoption of their offerings. And then third, which companies are seeing the highest churn rates, which of course is a silent killer of companies. And then finally, we're going to look at the sentiment and mindshare for two key areas that we like to cover often here on "Breaking Analysis", security and data. And data comprises database, including data warehousing, and then big data analytics is the second part of data. And then machine learning and AI is the third section within data that we're going to look at. Now, one other thing before we get into it, ETR very often will include open source offerings in the mix, even though they're not companies like TensorFlow or Kubernetes, for example. And we'll call that out during this discussion. The reason this is done is for context, because everyone is using open source. It is the heart of innovation and many business models are super glued to an open source offering, like take MariaDB, for example. There's the foundation and then there's with the open source code and then there, of course, the company that sells services around the offering. Okay, so let's first look at the highest and lowest sentiment among these private firms, the ones that have the highest mindshare. So they're naturally going to be somewhat larger. And we do this on two dimensions, sentiment on the vertical axis and mindshare on the horizontal axis and note the open source tool, see Kubernetes, Postgres, Kafka, TensorFlow, Jenkins, Grafana, et cetera. So Erik, please explain what we're looking at here, how it's derived and what the data tells us. >> Certainly, so there is a lot here, so we're going to break it down first of all by explaining just what mindshare and net sentiment is. You explain the axis. We have so many evaluation metrics, but we need to aggregate them into one so that way we can rank against each other. Net sentiment is really the aggregation of all the positive and subtracting out the negative. So the net sentiment is a very quick way of looking at where these companies stand versus their peers in their sectors and sub sectors. Mindshare is basically the awareness of them, which is good for very early stage companies. And you'll see some names on here that are obviously been around for a very long time. And they're clearly be the bigger on the axis on the outside. Kubernetes, for instance, as you mentioned, is open source. This de facto standard for all container orchestration, and it should be that far up into the right, because that's what everyone's using. In fact, the open source leaders are so prevalent in the emerging technology survey that we break them out later in our analysis, 'cause it's really not fair to include them and compare them to the actual companies that are providing the support and the security around that open source technology. But no survey, no analysis, no research would be complete without including these open source tech. So what we're looking at here, if I can just get away from the open source names, we see other things like Databricks and OneTrust . They're repeating as top net sentiment performers here. And then also the design vendors. People don't spend a lot of time on 'em, but Miro and Figma. This is their third survey in a row where they're just dominating that sentiment overall. And Adobe should probably take note of that because they're really coming after them. But Databricks, we all know probably would've been a public company by now if the market hadn't turned, but you can see just how dominant they are in a survey of nothing but private companies. And we'll see that again when we talk about the database later. >> And I'll just add, so you see automation anywhere on there, the big UiPath competitor company that was not able to get to the public markets. They've been trying. Snyk, Peter McKay's company, they've raised a bunch of money, big security player. They're doing some really interesting things in developer security, helping developers secure the data flow, H2O.ai, Dataiku AI company. We saw them at the Snowflake Summit. Redis Labs, Netskope and security. So a lot of names that we know that ultimately we think are probably going to be hitting the public market. Okay, here's the same view for private companies with less mindshare, Erik. Take us through this one. >> On the previous slide too real quickly, I wanted to pull that security scorecard and we'll get back into it. But this is a newcomer, that I couldn't believe how strong their data was, but we'll bring that up in a second. Now, when we go to the ones of lower mindshare, it's interesting to talk about open source, right? Kubernetes was all the way on the top right. Everyone uses containers. Here we see Istio up there. Not everyone is using service mesh as much. And that's why Istio is in the smaller breakout. But still when you talk about net sentiment, it's about the leader, it's the highest one there is. So really interesting to point out. Then we see other names like Collibra in the data side really performing well. And again, as always security, very well represented here. We have Aqua, Wiz, Armis, which is a standout in this survey this time around. They do IoT security. I hadn't even heard of them until I started digging into the data here. And I couldn't believe how well they were doing. And then of course you have AnyScale, which is doing a second best in this and the best name in the survey Hugging Face, which is a machine learning AI tool. Also doing really well on a net sentiment, but they're not as far along on that access of mindshare just yet. So these are again, emerging companies that might not be as well represented in the enterprise as they will be in a couple of years. >> Hugging Face sounds like something you do with your two year old. Like you said, you see high performers, AnyScale do machine learning and you mentioned them. They came out of Berkeley. Collibra Governance, InfluxData is on there. InfluxDB's a time series database. And yeah, of course, Alex, if you bring that back up, you get a big group of red dots, right? That's the bad zone, I guess, which Sisense does vis, Yellowbrick Data is a NPP database. How should we interpret the red dots, Erik? I mean, is it necessarily a bad thing? Could it be misinterpreted? What's your take on that? >> Sure, well, let me just explain the definition of it first from a data science perspective, right? We're a data company first. So the gray dots that you're seeing that aren't named, that's the mean that's the average. So in order for you to be on this chart, you have to be at least one standard deviation above or below that average. So that gray is where we're saying, "Hey, this is where the lump of average comes in. This is where everyone normally stands." So you either have to be an outperformer or an underperformer to even show up in this analysis. So by definition, yes, the red dots are bad. You're at least one standard deviation below the average of your peers. It's not where you want to be. And if you're on the lower left, not only are you not performing well from a utilization or an actual usage rate, but people don't even know who you are. So that's a problem, obviously. And the VCs and the PEs out there that are backing these companies, they're the ones who mostly are interested in this data. >> Yeah. Oh, that's great explanation. Thank you for that. No, nice benchmarking there and yeah, you don't want to be in the red. All right, let's get into the next segment here. Here going to look at evaluation rates, adoption and the all important churn. First new evaluations. Let's bring up that slide. And Erik, take us through this. >> So essentially I just want to explain what evaluation means is that people will cite that they either plan to evaluate the company or they're currently evaluating. So that means we're aware of 'em and we are choosing to do a POC of them. And then we'll see later how that turns into utilization, which is what a company wants to see, awareness, evaluation, and then actually utilizing them. That's sort of the life cycle for these emerging companies. So what we're seeing here, again, with very high evaluation rates. H2O, we mentioned. SecurityScorecard jumped up again. Chargebee, Snyk, Salt Security, Armis. A lot of security names are up here, Aqua, Netskope, which God has been around forever. I still can't believe it's in an Emerging Technology Survey But so many of these names fall in data and security again, which is why we decided to pick those out Dave. And on the lower side, Vena, Acton, those unfortunately took the dubious award of the lowest evaluations in our survey, but I prefer to focus on the positive. So SecurityScorecard, again, real standout in this one, they're in a security assessment space, basically. They'll come in and assess for you how your security hygiene is. And it's an area of a real interest right now amongst our ITDM community. >> Yeah, I mean, I think those, and then Arctic Wolf is up there too. They're doing managed services. You had mentioned Netskope. Yeah, okay. All right, let's look at now adoption. These are the companies whose offerings are being used the most and are above that standard deviation in the green. Take us through this, Erik. >> Sure, yet again, what we're looking at is, okay, we went from awareness, we went to evaluation. Now it's about utilization, which means a survey respondent's going to state "Yes, we evaluated and we plan to utilize it" or "It's already in our enterprise and we're actually allocating further resources to it." Not surprising, again, a lot of open source, the reason why, it's free. So it's really easy to grow your utilization on something that's free. But as you and I both know, as Red Hat proved, there's a lot of money to be made once the open source is adopted, right? You need the governance, you need the security, you need the support wrapped around it. So here we're seeing Kubernetes, Postgres, Apache Kafka, Jenkins, Grafana. These are all open source based names. But if we're looking at names that are non open source, we're going to see Databricks, Automation Anywhere, Rubrik all have the highest mindshare. So these are the names, not surprisingly, all names that probably should have been public by now. Everyone's expecting an IPO imminently. These are the names that have the highest mindshare. If we talk about the highest utilization rates, again, Miro and Figma pop up, and I know they're not household names, but they are just dominant in this survey. These are applications that are meant for design software and, again, they're going after an Autodesk or a CAD or Adobe type of thing. It is just dominant how high the utilization rates are here, which again is something Adobe should be paying attention to. And then you'll see a little bit lower, but also interesting, we see Collibra again, we see Hugging Face again. And these are names that are obviously in the data governance, ML, AI side. So we're seeing a ton of data, a ton of security and Rubrik was interesting in this one, too, high utilization and high mindshare. We know how pervasive they are in the enterprise already. >> Erik, Alex, keep that up for a second, if you would. So yeah, you mentioned Rubrik. Cohesity's not on there. They're sort of the big one. We're going to talk about them in a moment. Puppet is interesting to me because you remember the early days of that sort of space, you had Puppet and Chef and then you had Ansible. Red Hat bought Ansible and then Ansible really took off. So it's interesting to see Puppet on there as well. Okay. So now let's look at the churn because this one is where you don't want to be. It's, of course, all red 'cause churn is bad. Take us through this, Erik. >> Yeah, definitely don't want to be here and I don't love to dwell on the negative. So we won't spend as much time. But to your point, there's one thing I want to point out that think it's important. So you see Rubrik in the same spot, but Rubrik has so many citations in our survey that it actually would make sense that they're both being high utilization and churn just because they're so well represented. They have such a high overall representation in our survey. And the reason I call that out is Cohesity. Cohesity has an extremely high churn rate here about 17% and unlike Rubrik, they were not on the utilization side. So Rubrik is seeing both, Cohesity is not. It's not being utilized, but it's seeing a high churn. So that's the way you can look at this data and say, "Hm." Same thing with Puppet. You noticed that it was on the other slide. It's also on this one. So basically what it means is a lot of people are giving Puppet a shot, but it's starting to churn, which means it's not as sticky as we would like. One that was surprising on here for me was Tanium. It's kind of jumbled in there. It's hard to see in the middle, but Tanium, I was very surprised to see as high of a churn because what I do hear from our end user community is that people that use it, like it. It really kind of spreads into not only vulnerability management, but also that endpoint detection and response side. So I was surprised by that one, mostly to see Tanium in here. Mural, again, was another one of those application design softwares that's seeing a very high churn as well. >> So you're saying if you're in both... Alex, bring that back up if you would. So if you're in both like MariaDB is for example, I think, yeah, they're in both. They're both green in the previous one and red here, that's not as bad. You mentioned Rubrik is going to be in both. Cohesity is a bit of a concern. Cohesity just brought on Sanjay Poonen. So this could be a go to market issue, right? I mean, 'cause Cohesity has got a great product and they got really happy customers. So they're just maybe having to figure out, okay, what's the right ideal customer profile and Sanjay Poonen, I guarantee, is going to have that company cranking. I mean they had been doing very well on the surveys and had fallen off of a bit. The other interesting things wondering the previous survey I saw Cvent, which is an event platform. My only reason I pay attention to that is 'cause we actually have an event platform. We don't sell it separately. We bundle it as part of our offerings. And you see Hopin on here. Hopin raised a billion dollars during the pandemic. And we were like, "Wow, that's going to blow up." And so you see Hopin on the churn and you didn't see 'em in the previous chart, but that's sort of interesting. Like you said, let's not kind of dwell on the negative, but you really don't. You know, churn is a real big concern. Okay, now we're going to drill down into two sectors, security and data. Where data comprises three areas, database and data warehousing, machine learning and AI and big data analytics. So first let's take a look at the security sector. Now this is interesting because not only is it a sector drill down, but also gives an indicator of how much money the firm has raised, which is the size of that bubble. And to tell us if a company is punching above its weight and efficiently using its venture capital. Erik, take us through this slide. Explain the dots, the size of the dots. Set this up please. >> Yeah. So again, the axis is still the same, net sentiment and mindshare, but what we've done this time is we've taken publicly available information on how much capital company is raised and that'll be the size of the circle you see around the name. And then whether it's green or red is basically saying relative to the amount of money they've raised, how are they doing in our data? So when you see a Netskope, which has been around forever, raised a lot of money, that's why you're going to see them more leading towards red, 'cause it's just been around forever and kind of would expect it. Versus a name like SecurityScorecard, which is only raised a little bit of money and it's actually performing just as well, if not better than a name, like a Netskope. OneTrust doing absolutely incredible right now. BeyondTrust. We've seen the issues with Okta, right. So those are two names that play in that space that obviously are probably getting some looks about what's going on right now. Wiz, we've all heard about right? So raised a ton of money. It's doing well on net sentiment, but the mindshare isn't as well as you'd want, which is why you're going to see a little bit of that red versus a name like Aqua, which is doing container and application security. And hasn't raised as much money, but is really neck and neck with a name like Wiz. So that is why on a relative basis, you'll see that more green. As we all know, information security is never going away. But as we'll get to later in the program, Dave, I'm not sure in this current market environment, if people are as willing to do POCs and switch away from their security provider, right. There's a little bit of tepidness out there, a little trepidation. So right now we're seeing overall a slight pause, a slight cooling in overall evaluations on the security side versus historical levels a year ago. >> Now let's stay on here for a second. So a couple things I want to point out. So it's interesting. Now Snyk has raised over, I think $800 million but you can see them, they're high on the vertical and the horizontal, but now compare that to Lacework. It's hard to see, but they're kind of buried in the middle there. That's the biggest dot in this whole thing. I think I'm interpreting this correctly. They've raised over a billion dollars. It's a Mike Speiser company. He was the founding investor in Snowflake. So people watch that very closely, but that's an example of where they're not punching above their weight. They recently had a layoff and they got to fine tune things, but I'm still confident they they're going to do well. 'Cause they're approaching security as a data problem, which is probably people having trouble getting their arms around that. And then again, I see Arctic Wolf. They're not red, they're not green, but they've raised fair amount of money, but it's showing up to the right and decent level there. And a couple of the other ones that you mentioned, Netskope. Yeah, they've raised a lot of money, but they're actually performing where you want. What you don't want is where Lacework is, right. They've got some work to do to really take advantage of the money that they raised last November and prior to that. >> Yeah, if you're seeing that more neutral color, like you're calling out with an Arctic Wolf, like that means relative to their peers, this is where they should be. It's when you're seeing that red on a Lacework where we all know, wow, you raised a ton of money and your mindshare isn't where it should be. Your net sentiment is not where it should be comparatively. And then you see these great standouts, like Salt Security and SecurityScorecard and Abnormal. You know they haven't raised that much money yet, but their net sentiment's higher and their mindshare's doing well. So those basically in a nutshell, if you're a PE or a VC and you see a small green circle, then you're doing well, then it means you made a good investment. >> Some of these guys, I don't know, but you see these small green circles. Those are the ones you want to start digging into and maybe help them catch a wave. Okay, let's get into the data discussion. And again, three areas, database slash data warehousing, big data analytics and ML AI. First, we're going to look at the database sector. So Alex, thank you for bringing that up. Alright, take us through this, Erik. Actually, let me just say Postgres SQL. I got to ask you about this. It shows some funding, but that actually could be a mix of EDB, the company that commercializes Postgres and Postgres the open source database, which is a transaction system and kind of an open source Oracle. You see MariaDB is a database, but open source database. But the companies they've raised over $200 million and they filed an S-4. So Erik looks like this might be a little bit of mashup of companies and open source products. Help us understand this. >> Yeah, it's tough when you start dealing with the open source side and I'll be honest with you, there is a little bit of a mashup here. There are certain names here that are a hundred percent for profit companies. And then there are others that are obviously open source based like Redis is open source, but Redis Labs is the one trying to monetize the support around it. So you're a hundred percent accurate on this slide. I think one of the things here that's important to note though, is just how important open source is to data. If you're going to be going to any of these areas, it's going to be open source based to begin with. And Neo4j is one I want to call out here. It's not one everyone's familiar with, but it's basically geographical charting database, which is a name that we're seeing on a net sentiment side actually really, really high. When you think about it's the third overall net sentiment for a niche database play. It's not as big on the mindshare 'cause it's use cases aren't as often, but third biggest play on net sentiment. I found really interesting on this slide. >> And again, so MariaDB, as I said, they filed an S-4 I think $50 million in revenue, that might even be ARR. So they're not huge, but they're getting there. And by the way, MariaDB, if you don't know, was the company that was formed the day that Oracle bought Sun in which they got MySQL and MariaDB has done a really good job of replacing a lot of MySQL instances. Oracle has responded with MySQL HeatWave, which was kind of the Oracle version of MySQL. So there's some interesting battles going on there. If you think about the LAMP stack, the M in the LAMP stack was MySQL. And so now it's all MariaDB replacing that MySQL for a large part. And then you see again, the red, you know, you got to have some concerns about there. Aerospike's been around for a long time. SingleStore changed their name a couple years ago, last year. Yellowbrick Data, Fire Bolt was kind of going after Snowflake for a while, but yeah, you want to get out of that red zone. So they got some work to do. >> And Dave, real quick for the people that aren't aware, I just want to let them know that we can cut this data with the public company data as well. So we can cross over this with that because some of these names are competing with the larger public company names as well. So we can go ahead and cross reference like a MariaDB with a Mongo, for instance, or of something of that nature. So it's not in this slide, but at another point we can certainly explain on a relative basis how these private names are doing compared to the other ones as well. >> All right, let's take a quick look at analytics. Alex, bring that up if you would. Go ahead, Erik. >> Yeah, I mean, essentially here, I can't see it on my screen, my apologies. I just kind of went to blank on that. So gimme one second to catch up. >> So I could set it up while you're doing that. You got Grafana up and to the right. I mean, this is huge right. >> Got it thank you. I lost my screen there for a second. Yep. Again, open source name Grafana, absolutely up and to the right. But as we know, Grafana Labs is actually picking up a lot of speed based on Grafana, of course. And I think we might actually hear some noise from them coming this year. The names that are actually a little bit more disappointing than I want to call out are names like ThoughtSpot. It's been around forever. Their mindshare of course is second best here but based on the amount of time they've been around and the amount of money they've raised, it's not actually outperforming the way it should be. We're seeing Moogsoft obviously make some waves. That's very high net sentiment for that company. It's, you know, what, third, fourth position overall in this entire area, Another name like Fivetran, Matillion is doing well. Fivetran, even though it's got a high net sentiment, again, it's raised so much money that we would've expected a little bit more at this point. I know you know this space extremely well, but basically what we're looking at here and to the bottom left, you're going to see some names with a lot of red, large circles that really just aren't performing that well. InfluxData, however, second highest net sentiment. And it's really pretty early on in this stage and the feedback we're getting on this name is the use cases are great, the efficacy's great. And I think it's one to watch out for. >> InfluxData, time series database. The other interesting things I just noticed here, you got Tamer on here, which is that little small green. Those are the ones we were saying before, look for those guys. They might be some of the interesting companies out there and then observe Jeremy Burton's company. They do observability on top of Snowflake, not green, but kind of in that gray. So that's kind of cool. Monte Carlo is another one, they're sort of slightly green. They are doing some really interesting things in data and data mesh. So yeah, okay. So I can spend all day on this stuff, Erik, phenomenal data. I got to get back and really dig in. Let's end with machine learning and AI. Now this chart it's similar in its dimensions, of course, except for the money raised. We're not showing that size of the bubble, but AI is so hot. We wanted to cover that here, Erik, explain this please. Why TensorFlow is highlighted and walk us through this chart. >> Yeah, it's funny yet again, right? Another open source name, TensorFlow being up there. And I just want to explain, we do break out machine learning, AI is its own sector. A lot of this of course really is intertwined with the data side, but it is on its own area. And one of the things I think that's most important here to break out is Databricks. We started to cover Databricks in machine learning, AI. That company has grown into much, much more than that. So I do want to state to you Dave, and also the audience out there that moving forward, we're going to be moving Databricks out of only the MA/AI into other sectors. So we can kind of value them against their peers a little bit better. But in this instance, you could just see how dominant they are in this area. And one thing that's not here, but I do want to point out is that we have the ability to break this down by industry vertical, organization size. And when I break this down into Fortune 500 and Fortune 1000, both Databricks and Tensorflow are even better than you see here. So it's quite interesting to see that the names that are succeeding are also succeeding with the largest organizations in the world. And as we know, large organizations means large budgets. So this is one area that I just thought was really interesting to point out that as we break it down, the data by vertical, these two names still are the outstanding players. >> I just also want to call it H2O.ai. They're getting a lot of buzz in the marketplace and I'm seeing them a lot more. Anaconda, another one. Dataiku consistently popping up. DataRobot is also interesting because all the kerfuffle that's going on there. The Cube guy, Cube alum, Chris Lynch stepped down as executive chairman. All this stuff came out about how the executives were taking money off the table and didn't allow the employees to participate in that money raising deal. So that's pissed a lot of people off. And so they're now going through some kind of uncomfortable things, which is unfortunate because DataRobot, I noticed, we haven't covered them that much in "Breaking Analysis", but I've noticed them oftentimes, Erik, in the surveys doing really well. So you would think that company has a lot of potential. But yeah, it's an important space that we're going to continue to watch. Let me ask you Erik, can you contextualize this from a time series standpoint? I mean, how is this changed over time? >> Yeah, again, not show here, but in the data. I'm sorry, go ahead. >> No, I'm sorry. What I meant, I should have interjected. In other words, you would think in a downturn that these emerging companies would be less interesting to buyers 'cause they're more risky. What have you seen? >> Yeah, and it was interesting before we went live, you and I were having this conversation about "Is the downturn stopping people from evaluating these private companies or not," right. In a larger sense, that's really what we're doing here. How are these private companies doing when it comes down to the actual practitioners? The people with the budget, the people with the decision making. And so what I did is, we have historical data as you know, I went back to the Emerging Technology Survey we did in November of 21, right at the crest right before the market started to really fall and everything kind of started to fall apart there. And what I noticed is on the security side, very much so, we're seeing less evaluations than we were in November 21. So I broke it down. On cloud security, net sentiment went from 21% to 16% from November '21. That's a pretty big drop. And again, that sentiment is our one aggregate metric for overall positivity, meaning utilization and actual evaluation of the name. Again in database, we saw it drop a little bit from 19% to 13%. However, in analytics we actually saw it stay steady. So it's pretty interesting that yes, cloud security and security in general is always going to be important. But right now we're seeing less overall net sentiment in that space. But within analytics, we're seeing steady with growing mindshare. And also to your point earlier in machine learning, AI, we're seeing steady net sentiment and mindshare has grown a whopping 25% to 30%. So despite the downturn, we're seeing more awareness of these companies in analytics and machine learning and a steady, actual utilization of them. I can't say the same in security and database. They're actually shrinking a little bit since the end of last year. >> You know it's interesting, we were on a round table, Erik does these round tables with CISOs and CIOs, and I remember one time you had asked the question, "How do you think about some of these emerging tech companies?" And one of the executives said, "I always include somebody in the bottom left of the Gartner Magic Quadrant in my RFPs. I think he said, "That's how I found," I don't know, it was Zscaler or something like that years before anybody ever knew of them "Because they're going to help me get to the next level." So it's interesting to see Erik in these sectors, how they're holding up in many cases. >> Yeah. It's a very important part for the actual IT practitioners themselves. There's always contracts coming up and you always have to worry about your next round of negotiations. And that's one of the roles these guys play. You have to do a POC when contracts come up, but it's also their job to stay on top of the new technology. You can't fall behind. Like everyone's a software company. Now everyone's a tech company, no matter what you're doing. So these guys have to stay in on top of it. And that's what this ETS can do. You can go in here and look and say, "All right, I'm going to evaluate their technology," and it could be twofold. It might be that you're ready to upgrade your technology and they're actually pushing the envelope or it simply might be I'm using them as a negotiation ploy. So when I go back to the big guy who I have full intentions of writing that contract to, at least I have some negotiation leverage. >> Erik, we got to leave it there. I could spend all day. I'm going to definitely dig into this on my own time. Thank you for introducing this, really appreciate your time today. >> I always enjoy it, Dave and I hope everyone out there has a great holiday weekend. Enjoy the rest of the summer. And, you know, I love to talk data. So anytime you want, just point the camera on me and I'll start talking data. >> You got it. I also want to thank the team at ETR, not only Erik, but Darren Bramen who's a data scientist, really helped prepare this data, the entire team over at ETR. I cannot tell you how much additional data there is. We are just scratching the surface in this "Breaking Analysis". So great job guys. I want to thank Alex Myerson. Who's on production and he manages the podcast. Ken Shifman as well, who's just coming back from VMware Explore. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE. Does some great editing for us. Thank you. All of you guys. Remember these episodes, they're all available as podcast, wherever you listen. All you got to do is just search "Breaking Analysis" podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch david.vellante@siliconangle.com. You can DM me at dvellante or comment on my LinkedIn posts and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for Erik Bradley and The Cube Insights powered by ETR. Thanks for watching. Be well. And we'll see you next time on "Breaking Analysis". (upbeat music)

(upbeat music) >> When Oracle acquired Sun in 2009, it paid $5.6 billion net of Sun's cash and debt. Now I argued at the time that Oracle got one of the best deals in the history of enterprise tech, and I got a lot of grief for saying that because Sun had a declining business, it was losing money, and its revenue was under serious pressure as it tried to hang on for dear life. But Safra Catz understood that Oracle could pay Sun's lower profit and lagging businesses, like its low index 86 product lines, and even if Sun's revenue was cut in half, because Oracle has such a high revenue multiple as a software company, it could almost instantly generate $25 to $30 billion in shareholder value on paper. In addition, it was a catalyst for Oracle to initiate its highly differentiated engineering systems business, and was actually the precursor to Oracle's Cloud. Oracle saw that it could capture high margin dollars that used to go to partners like HP, it's original exit data partner, and get paid for the full stack across infrastructure, middleware, database, and application software, when eventually got really serious about cloud. Now there was also a major technology angle to this story. Remember Sun's tagline, "the network is the computer"? Well, they should have just called it cloud. Through the Sun acquisition. Oracle also got a couple of key technologies, Java, the number one programming language in the world, and MySQL, a key ingredient of the LAMP stack, that's Linux, Apache, MySQL and PHP, Perl or Python, on which the internet is basically built, and is used by many cloud services like Facebook, Twitter, WordPress, Flicker, Amazon, Aurora, and many other examples, including, by the way, Maria DB, which is a fork of MySQL created by MySQL's creator, basically in protest to Oracle's acquisition; the drama is Oscar worthy. It gets even better. In 2020, Oracle began introducing a new version of MySQL called MySQL HeatWave, and since late 2020 it's been in sort of a super cycle rolling, out three new releases in less than a year and a half in an attempt to expand its Tam and compete in new markets. Now we covered the release of MySQL Autopilot, which uses machine learning to automate management functions. And we also covered the bench marketing that Oracle produced against Snowflake, AWS, Azure, and Google. And Oracle's at it again with HeatWave, adding machine learning into its database capabilities, along with previously available integrations of OLAP and OLTP. This, of course, is in line with Oracle's converged database philosophy, which, as we've reported, is different from other cloud database providers, most notably Amazon, which takes the right tool for the right job approach and chooses database specialization over a one size fits all strategy. Now we've asked Oracle to come on theCUBE and explain these moves, and I'm pleased to welcome back Nipun Agarwal, who's the senior vice president for MySQL Database and HeatWave at Oracle. And today, in this video exclusive, we'll discuss machine learning, other new capabilities around elasticity and compression, and then any benchmark data that Nipun wants to share. Nipun's been a leading advocate of the HeatWave program. He's led engineering in that team for over 10 years, and he has over 185 patents in database technologies. Welcome back to the show Nipun. Great to see you again. Thanks for coming on. >> Thank you, Dave. Very happy to be back. >> Yeah, now for those who may not have kept up with the news, maybe to kick things off you could give us an overview of what MySQL HeatWave actually is so that we're all on the same page. >> Sure, Dave, MySQL HeatWave is a fully managed MySQL database service from Oracle, and it has a builtin query accelerator called HeatWave, and that's the part which is unique. So with MySQL HeatWave, customers of MySQL get a single database which they can use for transactional processing, for analytics, and for mixed workloads because traditionally MySQL has been designed and optimized for transaction processing. So in the past, when customers had to run analytics with the MySQL based service, they would need to move the data out of MySQL into some other database for running analytics. So they would end up with two different databases and it would take some time to move the data out of MySQL into this other system. With MySQL HeatWave, we have solved this problem and customers now have a single MySQL database for all their applications, and they can get the good performance of analytics without any changes to their MySQL application. >> Now it's no secret that a lot of times, you know, queries are not, you know, most efficiently written, and critics of MySQL HeatWave will claim that this product is very memory and cluster intensive, it has a heavy footprint that adds to cost. How do you answer that, Nipun? >> Right, so for offering any database service in the cloud there are two dimensions, performance and cost, and we have been very cognizant of both of them. So it is indeed the case that HeatWave is a, in-memory query accelerator, which is why we get very good performance, but it is also the case that we have optimized HeatWave for commodity cloud services. So for instance, we use the least expensive compute. We use the least expensive storage. So what I would suggest is for the customers who kind of would like to know what is the price performance advantage of HeatWave compared to any database we have benchmark against, Redshift, Snowflake, Google BigQuery, Azure Synapse, HeatWave is significantly faster and significantly lower price on a multitude of workloads. So not only is it in-memory database and optimized for that, but we have also optimized it for commodity cloud services, which makes it much lower price than the competition. >> Well, at the end of the day, it's customers that sort of decide what the truth is. So to date, what's been the customer reaction? Are they moving from other clouds from on-prem environments? Both why, you know, what are you seeing? >> Right, so we are definitely a whole bunch of migrations of customers who are running MySQL on-premise to the cloud, to MySQL HeatWave. That's definitely happening. What is also very interesting is we are seeing that a very large percentage of customers, more than half the customers who are coming to MySQL HeatWave, are migrating from other clouds. We have a lot of migrations coming from AWS Aurora, migrations from RedShift, migrations from RDS MySQL, TerriData, SAP HANA, right. So we are seeing migrations from a whole bunch of other databases and other cloud services to MySQL HeatWave. And the main reason we are told why customers are migrating from other databases to MySQL HeatWave are lower cost, better performance, and no change to their application because many of these services, like AWS Aurora are ETL compatible with MySQL. So when customers try MySQL HeatWave, not only do they get better performance at a lower cost, but they find that they can migrate their application without any changes, and that's a big incentive for them. >> Great, thank you, Nipun. So can you give us some names? Are there some real world examples of these customers that have migrated to MySQL HeatWave that you can share? >> Oh, absolutely, I'll give you a few names. Stutor.com, this is an educational SaaS provider raised out of Brazil. They were using Google BigQuery, and when they migrated to MySQL HeatWave, they found a 300X, right, 300 times improvement in performance, and it lowered their cost by 85 (audio cut out). Another example is Neovera. They offer cybersecurity solutions and they were running their application on an on-premise version of MySQL when they migrated to MySQL HeatWave, their application improved in performance by 300 times and their cost reduced by 80%, right. So by going from on-premise to MySQL HeatWave, they reduced the cost by 80%, improved performance by 300 times. We are Glass, another customer based out of Brazil. They were running on AWS EC2, and when they migrated, within hours they found that there was a significant improvement, like, you know, over 5X improvement in database performance, and they were able to accommodate a very large virtual event, which had more than a million visitors. Another example, Genius Senority. They are a game designer in Japan, and when they moved to MySQL HeatWave, they found a 90 times percent improvement in performance. And there many, many more like a lot of migrations, again, from like, you know, Aurora, RedShift and many other databases as well. And consistently what we hear is (audio cut out) getting much better performance at a much lower cost without any change to their application. >> Great, thank you. You know, when I ask that question, a lot of times I get, "Well, I can't name the customer name," but I got to give Oracle credit, a lot of times you guys have at your fingertips. So you're not the only one, but it's somewhat rare in this industry. So, okay, so you got some good feedback from those customers that did migrate to MySQL HeatWave. What else did they tell you that they wanted? Did they, you know, kind of share a wishlist and some of the white space that you guys should be working on? What'd they tell you? >> Right, so as customers are moving more data into MySQL HeatWave, as they're consolidating more data into MySQL HeatWave, customers want to run other kinds of processing with this data. A very popular one is (audio cut out) So we have had multiple customers who told us that they wanted to run machine learning with data which is stored in MySQL HeatWave, and for that they have to extract the data out of MySQL (audio cut out). So that was the first feedback we got. Second thing is MySQL HeatWave is a highly scalable system. What that means is that as you add more nodes to a HeatWave cluster, the performance of the system improves almost linearly. But currently customers need to perform some manual steps to add most to a cluster or to reduce the cluster size. So that was other feedback we got that people wanted this thing to be automated. Third thing is that we have shown in the previous results, that HeatWave is significantly faster and significantly lower price compared to competitive services. So we got feedback from customers that can we trade off some performance to get even lower cost, and that's what we have looked at. And then finally, like we have some results on various data sizes with TPC-H. Customers wanted to see if we can offer some more data points as to how does HeatWave perform on other kinds of workloads. And that's what we've been working on for the several months. >> Okay, Nipun, we're going to get into some of that, but, so how did you go about addressing these requirements? >> Right, so the first thing is we are announcing support for in-database machine learning, meaning that customers who have their data inside MySQL HeatWave can now run training, inference, and prediction all inside the database without the data or the model ever having to leave the database. So that's how we address the first one. Second thing is we are offering support for real time elasticity, meaning that customers can scale up or scale down to any number of nodes. This requires no manual intervention on part of the user, and for the entire duration of the resize operation, the system is fully available. The third, in terms of the costs, we have double the amount of data that can be processed per node. So if you look at a HeatWave cluster, the size of the cluster determines the cost. So by doubling the amount of data that can be processed per node, we have effectively reduced the cluster size which is required for planning a given workload to have, which means it reduces the cost to the customer by half. And finally, we have also run the TPC-DS workload on HeatWave and compared it with other vendors. So now customers can have another data point in terms of the performance and the cost comparison of HeatWave with other services. >> All right, and I promise, I'm going to ask you about the benchmarks, but I want to come back and drill into these a bit. How is HeatWave ML different from competitive offerings? Take for instance, Redshift ML, for example. >> Sure, okay, so this is a good comparison. Let's start with, let's say RedShift ML, like there are some systems like, you know, Snowflake, which don't even offer any, like, processing of machine learning inside the database, and they expect customers to write a whole bunch of code, in say Python or Java, to do machine learning. RedShift ML does have integration with SQL. That's a good start. However, when customers of Redshift need to run machine learning, and they invoke Redshift ML, it makes a call to another service, SageMaker, right, where so the data needs to be exported to a different service. The model is generated, and the model is also outside RedShift. With HeatWave ML, the data resides always inside the MySQL database service. We are able to generate models. We are able to train the models, run inference, run explanations, all inside the MySQL HeatWave service. So the data, or the model, never have to leave the database, which means that both the data and the models can now be secured by the same access control mechanisms as the rest of the data. So that's the first part, that there is no need for any ETL. The second aspect is the automation. Training is a very important part of machine learning, right, and it impacts the quality of the predictions and such. So traditionally, customers would employ data scientists to influence the training process so that it's done right. And even in the case of Redshift ML, the users are expected to provide a lot of parameters to the training process. So the second thing which we have worked on with HeatWave ML is that it is fully automated. There is absolutely no user intervention required for training. Third is in terms of performance. So one of the things we are very, very sensitive to is performance because performance determines the eventual cost to the customer. So again, in some benchmarks, which we have published, and these are all available on GitHub, we are showing how HeatWave ML is 25 times faster than Redshift ML, and here's the kicker, at 1% of the cost. So four benefits, the data all remain secure inside the database service, it's fully automated, much faster, much lower cost than the competition. >> All right, thank you Nipun. Now, so there's a lot of talk these days about explainability and AI. You know, the system can very accurately tell you that it's a cat, you know, or for you Silicon Valley fans, it's a hot dog or not a hot dog, but they can't tell you how the system got there. So what is explainability, and why should people care about it? >> Right, so when we were talking to customers about what they would like from a machine learning based solution, one of the feedbacks we got is that enterprise is a little slow or averse to uptaking machine learning, because it seems to be, you know, like magic, right? And enterprises have the obligation to be able to explain, or to provide a answer to their customers as to why did the database make a certain choice. With a rule based solution it's simple, it's a rule based thing, and you know what the logic was. So the reason explanations are important is because customers want to know why did the system make a certain prediction? One of the important characteristics of HeatWave ML is that any model which is generated by HeatWave ML can be explained, and we can do both global explanations or model explanations as well as we can also do local explanations. So when the system makes a specific prediction using HeatWave ML, the user can find out why did the system make such a prediction? So for instance, if someone is being denied a loan, the user can figure out what were the attribute, what were the features which led to that decision? So this ensures, like, you know, fairness, and many of the times there is also like a need for regulatory compliance where users have a right to know. So we feel that explanations are very important for enterprise workload, and that's why every model which is generated by HeatWave ML can be explained. >> Now I got to give Snowflakes some props, you know, this whole idea of separating compute from storage, but also bringing the database to the cloud and driving elasticity. So that's been a key enabler and has solved a lot of problems, in particular the snake swallowing the basketball problem, as I often say. But what about elasticity and elasticity in real time? How is your version, and there's a lot of companies chasing this, how is your approach to an elastic cloud database service different from what others are promoting these days? >> Right, so a couple of characteristics. One is that we have now fully automated the process of elasticity, meaning that if a user wants to scale up or scale down, the only thing they need to specify is the eventual size of the cluster and the system completely takes care of it transparently. But then there are a few characteristics which are very unique. So for instance, we can scale up or scale down to any number of nodes. Whereas in the case of Snowflake, the number of nodes someone can scale up or scale down to are the powers of two. So if a user needs 70 CPUs, well, their choice is either 64 or 128. So by providing this flexibly with MySQL HeatWave, customers get a custom fit. So they can get a cluster which is optimized for their specific portal. So that's the first thing, flexibility of scaling up or down to any number of nodes. The second thing is that after the operation is completed, the system is fully balanced, meaning the data across the various nodes is fully balanced. That is not the case with many solutions. So for instance, in the case of Redshift, after the resize operation is done, the user is expected to manually balance the data, which can be very cumbersome. And the third aspect is that while the resize operation is going on, the HeatWave cluster is completely available for queries, for DMLS, for loading more data. That is, again, not the case with Redshift. Redshift, suppose the operation takes 10 to 15 minutes, during that window of time, the system is not available for writes, and for a big part of that chunk of time, the system is not even available for queries, which is very limiting. So the advantages we have are fully flexible, the system is in a balanced state, and the system is completely available for the entire duration operation. >> Yeah, I guess you got that hypergranularity, which, you know, sometimes they say, "Well, t-shirt sizes are good enough," but then I think of myself, some t-shirts fit me better than others, so. Okay, I saw on the announcement that you have this lower price point for customers. How did you actually achieve this? Could you give us some details around that please? >> Sure, so there are two things for announcing this service, which lower the cost for the customers. The first thing is that we have doubled the amount of data that can be processed by a HeatWave node. So if we have doubled the amount of data, which can be a process by a node, the cluster size which is required by customers reduces to half, and that's why the cost drops to half. The way we have managed to do this is by two things. One is support for Bloom filters, which reduces the amount of intermediate memory. And second is we compress the base data. So these are the two techniques we have used to process more data per node. The second way by which we are lowering the cost for the customers is by supporting pause and resume of HeatWave. And many times you find customers of like HeatWave and other services that they want to run some other queries or some other workloads for some duration of time, but then they don't need the cluster for a few hours. Now with the support for pause and resume, customers can pause the cluster and the HeatWave cluster instantaneously stops. And when they resume, not only do we fetch the data, in a very, like, you know, a quick pace from the object store, but we also preserve all the statistics, which are used by Autopilot. So both the data and the metadata are fetched, extremely fast from the object store. So with these two capabilities we feel that it'll drive down the cost to our customers even more. >> Got it, thank you. Okay, I promised I was going to get to the benchmarks. Let's have it. How do you compare with others but specifically cloud databases? I mean, and how do we know these benchmarks are real? My friends at EMC, they were back in the day, they were brilliant at doing benchmarks. They would produce these beautiful PowerPoints charts, but it was kind of opaque, but what do you say to that? >> Right, so there are multiple things I would say. The first thing is that this time we have published two benchmarks, one is for machine learning and other is for SQL analytics. All the benchmarks, including the scripts which we have used are available on GitHub. So we have full transparency, and we invite and encourage customers or other service providers to download the scripts, to download the benchmarks and see if they get any different results, right. So what we are seeing, we have published it for other people to try and validate. That's the first part. Now for machine learning, there hasn't been a precedence for enterprise benchmarks so we talk about aiding open data sets and we have published benchmarks for those, right? So both for classification, as well as for aggression, we have run the training times, and that's where we find that HeatWave MLS is 25 times faster than RedShift ML at one percent of the cost. So fully transparent, available. For SQL analytics, in the past we have shown comparisons with TPC-H. So we would show TPC-H across various databases, across various data sizes. This time we decided to use TPC-DS. the advantage of TPC-DS over TPC-H is that it has more number of queries, the queries are more complex, the schema is more complex, and there is a lot more data skew. So it represents a different class of workloads, and which is very interesting. So these are queries derived from the TPC-DS benchmark. So the numbers we have are published this time are for 10 terabyte TPC-DS, and we are comparing with all the four majors services, Redshift, Snowflake, Google BigQuery, Azure Synapse. And in all the cases, HeatWave is significantly faster and significantly lower priced. Now one of the things I want to point out is that when we are doing the cost comparison with other vendors, we are being overly fair. For instance, the cost of HeatWave includes the cost of both the MySQL node as well as the HeatWave node, and with this setup, customers can run transaction processing analytics as well as machine learning. So the price captures all of it. Whereas with the other vendors, the comparison is only for the analytic queries, right? So if customers wanted to run RDP, you would need to add the cost of that database. Or if customers wanted to run machine learning, you would need to add the cost of that service. Furthermore, with the case of HeatWave, we are quoting pay as you go price, whereas for other vendors like, you know, RedShift, and like, you know, where applicable, we are quoting one year, fully paid upfront cost rate. So it's like, you know, very fair comparison. So in terms of the numbers though, price performance for TPC-DS, we are about 4.8 times better price performance compared to RedShift We are 14.4 times better price performance compared to Snowflake, 13 times better than Google BigQuery, and 15 times better than Synapse. So across the board, we are significantly faster and significantly lower price. And as I said, all of these scripts are available in GitHub for people to drive for themselves. >> Okay, all right, I get it. So I think what you're saying is, you could have said this is what it's going to cost for you to do both analytics and transaction processing on a competitive platform versus what it takes to do that on Oracle MySQL HeatWave, but you're not doing that. You're saying, let's take them head on in their sweet spot of analytics, or OLTP separately and you're saying you still beat them. Okay, so you got this one database service in your cloud that supports transactions and analytics and machine learning. How much do you estimate your saving companies with this integrated approach versus the alternative of kind of what I called upfront, the right tool for the right job, and admittedly having to ETL tools. How can you quantify that? >> Right, so, okay. The numbers I call it, right, at the end of the day in a cloud service price performance is the metric which gives a sense as to how much the customers are going to save. So for instance, for like a TPC-DS workload, if we are 14 times better price performance than Snowflake, it means that our cost is going to be 1/14th for what customers would pay for Snowflake. Now, in addition, in other costs, in terms of migrating the data, having to manage two different databases, having to pay for other service for like, you know, machine learning, that's all extra and that depends upon what tools customers are using or what other services they're using for transaction processing or for machine learning. But these numbers themselves, right, like they're very, very compelling. If we are 1/5th the cost of Redshift, right, or 1/14th of Snowflake, these numbers, like, themselves are very, very compelling. And that's the reason we are seeing so many of these migrations from these databases to MySQL HeatWave. >> Okay, great, thank you. Our last question, in the Q3 earnings call for fiscal 22, Larry Ellison said that "MySQL HeatWave is coming soon on AWS," and that caught a lot of people's attention. That's not like Oracle. I mean, people might say maybe that's an indication that you're not having success moving customers to OCI. So you got to go to other clouds, which by the way I applaud, but any comments on that? >> Yep, this is very much like Oracle. So if you look at one of the big reasons for success of the Oracle database and why Oracle database is the most popular database is because Oracle database runs on all the platforms, and that has been the case from day one. So very akin to that, the idea is that there's a lot of value in MySQL HeatWave, and we want to make sure that we can offer same value to the customers of MySQL running on any cloud, whether it's OCI, whether it's the AWS, or any other cloud. So this shows how confident we are in our offering, and we believe that in other clouds as well, customers will find significant advantage by having a single database, which is much faster and much lower price then what alternatives they currently have. So this shows how confident we are about our products and services. >> Well, that's great, I mean, obviously for you, you're in MySQL group. You love that, right? The more places you can run, the better it is for you, of course, and your customers. Okay, Nipun, we got to leave it there. As always it's great to have you on theCUBE, really appreciate your time. Thanks for coming on and sharing the new innovations. Congratulations on all the progress you're making here. You're doing a great job. >> Thank you, Dave, and thank you for the opportunity. >> All right, and thank you for watching this CUBE conversation with Dave Vellante for theCUBE, your leader in enterprise tech coverage. We'll see you next time. (upbeat music)

>> Narrator: From around the globe, it's theCUBE. With digital coverage of IBM Think 2021. Brought to you by IBM. >> Welcome back to IBM Think 2021. This is theCUBE's continuous virtual in-depth coverage of the people, processes, and technologies that are changing our world. Right now we're going to talk about modernization and the Synergy with Cloud. And we're pleased to welcome Doug Armbrust, who's the VP GTS Cloud Synergy. Hey Doug, how you doing? >> Great, Dave. I'm excited to be on theCUBE, thanks for having me. >> It's our pleasure. Hey, let's talk a little bit of tech. What are some of the technologies that your clients are applying on their path to modernization? >> Sure. I'll give you three examples and three that we're seeing a lot of interest in from a services standpoint. One is automation. Automation is an area that's been a focus for Several decades but We're seeing a renewed excitement around the opportunity for automated operations. Really, I'll talk about two other technologies but the extension of automation and to some of the newer cloud technologies. So that's one. Two is cloud. Cloud has been a terminal industry for a while now and folks have been at various points of a journey to cloud-centric models and technologies. We're seeing an even accelerated transition to not just public cloud but also private cloud technologies, and in particular, need to interconnect those with one another and with a traditional environments. The last one, I think there's been a bit of a referendum on the technology over the last year is around containers, specifically Kubernetes, as a standard for that space. A cementing of direction around containers. Clearly, people are different stages of implementation and experimentation with the technology but I do see a referendum on this being a fundamental part of future technology and direction. >> So, okay. So automation, cloud, and containers. I'm going to ask you a follow up on containers because it's clear that when you look at all the data, it's off the charts in terms of adoption and ultimately our scenario is okay, it gets subsumed into the stack. But where Where the customers ultimately want to go? Obviously, they're upskilling but what's the outcome that they're trying to achieve? >> Yeah, it's a good question. General question of the ask a modernization. I like modern things. We'd like to live in a modern house, my wife likes a farmhouse so guess where we live. (laughs loudly) We live in a farm house with Modernized appliances and infrastructure. >> New cost to live with. (laughs loudly) >> Ultimately, enterprises, they're working back from an objective, and that objective, had this term digital transformation for about a decade. Underneath that umbrella, it's about being able to move and respond quickly. It's about being able to create innovation and accelerate innovation. I think probably most important is deliver on a customer experience and end customer experience. 10 years ago, what I expected when I went to a restaurant was a If I could look them up on the internet and find their location, use my GPS, get there, I was good to go. A year ago, I'm looking for Use an app, them to remember my favorite place to sit. Very different expectations and that pressure on enterprise, to meet those end expectations is really at the heart of The modernization and part of that's Infrastructure modernization containers is interesting because it brings together, not just infrastructure, brings together how application development cycles are being implemented. It has implications for security that Can be positive if done right. We do see that as A key area to meet the end and business objectives. It's going to take some time. IDC, I think is the most bullish. They took like 80% of workloads. By 2023, we'll shift to containers. I believe that for newly created workloads. I think developers have got this in their hands and they understand the efficiencies for their own work as well as when this moves to production. This sort of DevSecOps model, kind of comes with containers if done right. There's a legacy that's going to be around a long time, helping customers understand those operating models and how to live with them both is going to be important over the next five to 10 years. >> You're talking about those drivers responsiveness, the innovation, et cetera. I live in an old house too and there's another component here which is that 80%, reasonable people could discuss that, because there's a risk component, right? I can modernize my house but I could jack up one into the house but it might mess up something that I just did. And so, CIO is obviously a risk-averse, they want to modernize but at the same time, they want to get from point a to point b with minimum disruption. To that end, I wonder if you could talk about what you saw during the pandemic. We're still in the pandemic but you had a reduction in budgets, virtually across the board, minus four, minus 5% in spending, had a shift toward work from home, whatever, VDI, laptops, rushed endpoint security, that whole thing. A lot of organizations try to do both. They said, "Hey, we're actually going to double down on digital transformation." We see this as a lean and opportunity. We got liquidity. How did COVID influence modernization initiatives in your client base? >> It impacted different clients in different ways. Some, as you mentioned, I almost view it as very Darwinian in the sense that those who had modernized and had capabilities, more deeply automated were ready for the transition that they had to go through so they were able to quickly shift to work from home. They were able to deliver on new client experiences, the analogy before in digital transformation, those pressures never went away, but COVID just brought new ones, and they expected all of those things but now they expected the restaurant They expect the restaurant to bring that food to my door and do it in a safe manner. The challenges it brought on organizations were In many cases, new. Some who were in a good position could accelerate work in place and leverage that. Others had a harder time, right? Those who couldn't translate technology to immediate returns, to kind of fuel that ongoing progress, had to make some hard decisions. I would say that's probably the single trend, projects are very carefully reviewed. There's that view of "Will this help me now and into the future?" That's always present but it's present in a stronger manner than we would've have seen it for some time. In that envelope, can I come back to within those three technologies? Automation has certainly We've seen a jump because of its nature. What we see in automation projects is A faster time to implement and achieve some of the agility and flexibility that cloud provides but can take a longer timeframe if you haven't gotten far along in your cloud journey. Containers, even longer timeframe. So a lot of folks are looking at automation projects, particularly those that weren't as well positioned for sort of a quick turn and then taking that automation work and extending it into cloud and containers, as those initiatives progress. >> There are definitely some historical parallels and I could even go back to Y2K and look at all the application rationalization exercises that were going on back then. The technologies were different. You didn't have the modern cloud, containers have been around forever but not in the form of Kubernetes. The automation was scary back then but nonetheless, people were trying to use scripts or whatever they could do. But now, it's almost like an automation mandate, if you were in a digital business, you were out of business. So what are the What are some of the learnings that you've seen from these modernization journeys that you're taking customers on that you might be able to share. >> Let me comment on automation first, I'll say it more generally. I think automation, you're right, we're not finding enterprises that are doing things manually. Everybody's gotten at least to kind of that scripting point. And then we see That has its own journey. Then there's centralization and folks trusting the automation to enable self-service. That's sort of a Kind of a tipping point to who is ready for COVID and who wasn't. Those who had hardened their automation to enable self-service generally could then call on that self service to meet the new demands that they were facing. The next stage and we see less folks there, we get into this sort of Infrastructure as code. We talk about areas of intelligence in your automation. You talk about trust, not as many have progressed to where they trust their automation to Proactively, maybe sometimes reactively respond to a situation or set of You have to be very integrated at that point and you have to really believe in your automation. You then talk about integrating AI to sense, respond, make decisions and bring those back into your automation technologies. I'd say, that's still very future but folks are very intrigued by that. Your more general question, what's sort of some of the learnings. Really goes back to Modernization needs to have a business school. That's become maybe more clear than it was a year and a half ago. In the absence of that, IT projects have always had some degree of failure. It's just the evidence of that failures, probably a little bit more poignant. Related to that, is there needs to be a strategic plan and in particular with modernization, it's easy to get caught up with the modern side. And Dave, you were kind of alluded to this before. If you're not thinking about the old, the connection to the legacy, that's a very common kind of failure signature. It's a marching ahead with the modernization, without a strategic plan and connect those things and an ability to kind of tackle a piece at a time. Sometimes budgets go away and that's a problem. Each step in the journey is really the third lesson. Needs to have incremental value. It needs to kind of pay back something to help fund the next stage of modernization. I'd say the last one and it's self-serving for us as a services company. It's helpful to have a partner on these journeys. In my particular area of focus, in a year and a half, we've had 1,600 engagements. A lot of those engagements are people coming to us after making what they now view as mistakes. Some of the three areas I just mentioned. And being able to bring somebody in with experience with maybe some complimentary skills that can partner within an enterprise can be very helpful to avoid some of the pitfalls. >> I think, your point is right on. I've seen horror stories where people Literally, we're going to go off the mainframe. They got decades old COBOL code that's working just fine and they literally risked their business trying to brute force migrate off and they never could We're not going to freeze the code. It's just horror stories. But today's different, you can actually build an abstraction layer, leverage cloud services, and Kubernetes, and the like, use microservices to actually connect the old to the new. And that's the hardest part, again, old house analogies. I've done a lot of connecting the old to the new, that's the hardest part. You got to be really careful but today the technologies are enabling to do that and one of them is Obviously, things like OpenShift. The definition of open, again, a little history here, it used to be Unix was open and then Windows and then Linux, the LAMP stack. But really That piece of your portfolio is a critical part to enable these types of moves. >> Absolutely. It's exciting that technologies are there and there's a path forward. And it's great to Great to work with a partner, who's maybe, done that 10 or 15 times, or more and have them help guide you on that path. But the good news is there is Enabling technologies to transform in a number of ways, depending on what the business objectives are for an enterprise. >> Cool. All right, Doug, we've got to go. Thanks so much for coming on theCUBE. It's great to see you. >> Okay, same Dave. >> All right. >> Appreciate it. >> Keep it right there everybody. This is Dave Vellante. You're watching IBM Think 2021. The virtual edition covered on theCUBE. (bouncy music)

(bright upbeat music) >> Hello everyone, and welcome to the special exclusive CUBE Conversation, where we continue our coverage of the trends of the database market. With me is Nipun Agarwal, who's the vice president, MySQL HeatWave in advanced development at Oracle. Nipun, welcome. >> Thank you Dave. >> I love to have technical people on the Cube to educate, debate, inform, and we've extensively covered this market. We were all over the Snowflake IPO and at that time I remember, I challenged organizations bring your best people. Because I want to better understand what's happening at Database. After Oracle kind of won the Database wars 20 years ago, Database kind of got boring. And then it got really exciting with the big data movement, and all the, not only SQL stuff coming out, and Hadoop and blah, blah, blah. And now it's just exploding. You're seeing huge investments from many of your competitors, VCs are trying to get into the action. Meanwhile, as I've said many, many times, your chairman and head of technology, CTO, Larry Ellison, continues to invest to keep Oracle relevant. So it's really been fun to watch and I really appreciate you coming on. >> Sure thing. >> We have written extensively, we talked to a lot of Oracle customers. You get the leading mission critical database in the world. Everybody from Fortune 100, we evaluated what Gardner said about the operational databases. I think there's not a lot of question there. And we've written about that on WikiBound about you're converged databases, and the strategy there, and we're going to get into that. We've covered Autonomous Data Warehouse Exadata Cloud at Customer, and then we just want to really try to get into your area, which has been, kind of caught our attention recently. And I'm talking about the MySQL Database Service with HeatWave. I love the name, I laugh. It was an unveiled, I don't know, a few months ago. So Nipun, let's start the discussion today. Maybe you can update our viewers on what is HeatWave? What's the overall focus with Oracle? And how does it fit into the Cloud Database Service? >> Sure Dave. So HeatWave is a in-memory query accelerator for the MySQL Database Service for speeding up analytic queries as well as long running complex OLTP queries. And this is all done in the context of a single database which is the MySQL Database Service. Also, all existing MySQL applications or MySQL compatible tools and applications continue to work as is. So there is no change. And with this HeatWave, Oracle is delivering the only MySQL service which provides customers with a single unified platform for both analytic as well as transaction processing workloads. >> Okay, so, we've seen open source databases in the cloud growing very rapidly. I mentioned Snowflake, I think Google's BigQuery, get some mention, we'll talk, we'll maybe talk more about Redshift later on, but what I'm wondering, well let's talk about now, how does MySQL HeatWave service, how does that compare to MySQL-based services from other cloud vendors? I can get MySQL from others. In fact, I think we do. I think we run WikiBound on the LAMP stack. I think it's running on Amazon, but so how does your service compare? >> No other vendor, like, no other vendor offers this differentiated solution with an open source database namely, having a single database, which is optimized both for transactional processing and analytics, right? So the example is like MySQL. A lot of other cloud vendors provide MySQL service but MySQL has been optimized for transaction processing so when customs need to run analytics they need to move the data out of MySQL into some other database for any analytics, right? So we are the only vendor which is now offering this unified solution for both transactional processing analytics. That's the first point. Second thing is, most of the vendors out there have taken open source databases and they're basically hosting it in the cloud. Whereas HeatWave, has been designed from the ground up for the cloud, and it is a 100% compatible with MySQL applications. And the fact that we have designed it from the ground up for the cloud, maybe I'll spend 100s of person years of research and engineering means that we have a solution, which is very, very scalable, it's very optimized in terms of performance, and it is very inexpensive in terms of the cost. >> Are you saying, well, wait, are you saying that you essentially rewrote MySQL to create HeatWave but at the same time maintained compatibility with existing applications? >> Right. So we enhanced MySQL significantly and we wrote a whole bunch of new code which is brand new code optimized for the cloud in such a manner that yes, it is 100% compatible with all existing MySQL applications. >> What does it mean? And if I'm to optimize for the cloud, I mean, I hear that and I say, okay, it's taking advantage of cloud-native. I hear kind of the buzzwords, cloud-first, cloud-native. What does it specifically mean from a technical standpoint? >> Right. So first, let's talk about performance. What we have done is that we have looked at two aspects. We have worked with shapes like for instance, like, the compute shapes which provide the best performance for dollar, per dollar. So I'll give you a couple of examples. We have optimized for certain shifts. So, HeatWave is in-memory query accelerator. So the cost of the system is dominated by the cost. So we are working with chips which provide the cheapest cost per terabyte of memory. Secondly, we are using commodity cloud services in such a manner that it's in-optimized for both performance as well as performance per dollar. So, example is, we are not using any locally-attached SSDs. We use ObjectStore because it's very inexpensive. And then I guess at some point I will get into the details of the architecture. The system has been really, really designed for massive scalability. So as you add more compute, as you add more service, the system continues to scale almost perfectly linearly. So this is what I mean in terms of being optimized for the cloud. >> All right, great. >> And furthermore, (indistinct). >> Thank you. No, carry on. >> Over the next few months, you will see a bunch of other announcements where we're adding a whole bunch of machine learning and data driven-based automation which we believe is critical for the cloud. So optimized for performance, optimized for the cloud, and machine learning-based automation which we believe is critical for any good cloud-based service. >> All right, I want to come back and ask you more about the architecture, but you mentioned some of the others taking open source databases and shoving them into the cloud. Let's take the example of AWS. They have a series of specialized data stores and, for different workloads, Aurora is for OLTP I actually think it's based on MySQL Redshift which is based on ParAccel. And so, and I've asked Amazon about this, and their response is, actually kind of made sense to me. Look, we want the right tool for the right job, we want access to the primitives because when the market changes we can change faster as opposed to, if we put, if we start building bigger and bigger databases with more functionality, it's, we're not as agile. So that kind of made sense to me. I know we, again, we use a lot, we use, I think I said MySQL in Amazon we're using DynamoDB, works, that's cool. We're not huge. And I, we fully admit and we've researched this, when you start to get big that starts to get maybe expensive. But what do you think about that approach and why is your approach better? >> Right, we believe that there are multiple drawbacks of having different databases or different services, one, optimized for transactional processing and one for analytics and having to ETL between these different services. First of all, it's expensive because you have to manage different databases. Secondly, it's complex. From an application standpoint, applications need, now need to understand the semantics of two different databases. It's inefficient because you have to transfer data at some PRPC from one database to the other one. It's not secure because there is security aspects involved when your transferring data and also the identity of users in the two different databases is different. So it's, the approach which has been taken by Amazons and such, we believe, is more costly, complex, inefficient and not secure. Whereas with HeatWave, all the data resides in one database which is MySQL and it can run both transaction processing and analytics. So in addition to all the benefits I talked about, customers can also make their decisions in real time because there is no need to move the data. All the data resides in a single database. So as soon as you make any changes, those changes are visible to customers for queries right away, which is not the case when you have different siloed specialized databases. >> Okay, that, a lot of ways to skin a cat and that what you just said makes sense. By the way, we were saying before, companies have taken off the shelf or open source database has shoved them in the cloud. I have to give Amazon some props. They actually have done engineering to Aurora and Redshift. And they've got the engineering capabilities to do that. But you can see, for example, in Redshift the way they handle separating compute from storage it's maybe not as elegant as some of the other players like a Snowflake, for example, but they get there and they, maybe it's a little bit more brute force but so I don't want to just make it sound like they're just hosting off the shelf in the cloud. But is it fair to say that there's like a crossover point? So in other words, if I'm smaller and I'm not, like doing a bunch of big, like us, I mean, it's fine. It's easy, I spin it up. It's cheaper than having to host my own servers. So there's, presumably there's a sweet spot for that approach and a sweet spot for your approach. Is that fair or do you feel like you can cover a wider spectrum? >> We feel we can cover the entire spectrum, not wider, the entire spectrum. And we have benchmarks published which are actually available on GitHub for anyone to try. You will see that this approach you have taken with the MySQL Database Service in HeatWave, we are faster, we are cheaper without having to move the data. And the mileage or the amount of improvement you will get, surely vary. So if you have less data the amount of improvement you will get, maybe like say 100 times, right, or 500 times, but smaller data sizes. If you get to lots of data sizes this improvement amplifies to 1000 times or 10,000 times. And similarly for the cost, if the data size is smaller, the cost advantage you will have is less, maybe MySQL HeatWave is one third the cost. If the data size is larger, the cost advantage amplifies. So to your point, MySQL Database Service in HeatWave is going to be better for all sizes but the amount of mileage or the amount of benefit you will get increases as the size of the data increases. >> Okay, so you're saying you got better performance, better cost, better price performance. Let me just push back a little bit on this because I, having been around for awhile, I often see these performance and price comparisons. And what often happens is a vendor will take the latest and greatest, the one they just announced and they'll compare it to an N-1 or an N-2, running on old hardware. So, is, you're normalizing for that, is that the game you're playing here? I mean, how can you, give us confidence that this is easier kind of legitimate benchmarks in your GitHub repo. >> Absolutely. I'll give you a bunch of like, information. But let me preface this by saying that all of our scripts are available in the open source in the GitHub repo for anyone to try and we would welcome feedback otherwise. So we have taken, yes, the latest version of MySQL Database Service in HeatWave, we have optimized it, and we have run multiple benchmarks. For instance, TBC-H, TPC-DS, right? Because the amount of improvement a query will get depends upon the specific query, depends upon the predicates, it depends on the selectivity so we just wanted to use standard benchmarks. So it's not the case that if you're using certain classes of query, excuse me, benefit, get them more. So, standard benchmarks. Similarly, for the other vendors or other services like Redshift, we have run benchmarks on the latest shapes of Redshift the most optimized configuration which they recommend, running their scripts. So this is not something that, hey, we're just running out of the box. We have optimized Aurora, we have optimized (indistinct) to the best and possible extent we can based on their guidelines, based on their latest release, and that's what you're talking about in terms of the numbers. >> All right. Please continue. >> Now, for some other vendors, if we get to the benchmark section, we'll talk about, we are comparing with other services, let's say Snowflake. Well there, there are issues in terms of you can't legally run Snowflake numbers, right? So there, we have looked at some reports published by Gigaom report. and we are taking the numbers published by the Gigaom report for Snowflake, Google BigQuery and as you'll see maps numbers, right? So those, we have not won ourselves. But for AWS Redshift, as well as AWS Aurora, we have run the numbers and I believe these are the best numbers anyone can get. >> I saw that Gigaom report and I got to say, Gigaom, sometimes I'm like, eh, but I got to say that, I forget the guy's name, he knew what he was talking about. He did a good job, I thought. I was curious as to the workload. I always say, well, what's the workload. And, but I thought that report was pretty detailed. And Snowflake did not look great in that report. Oftentimes, and they've been marketing the heck out of it. I forget who sponsored it. It is, it was sponsored content. But, I did, I remember seeing that and thinking, hmm. So, I think maybe for Snowflake that sweet spot is not, maybe not that performance, maybe it's the simplicity and I think that's where they're making their mark. And most of their databases are small and a lot of read-only stuff. And so they've found a market there. But I want to come back to the architecture and really sort of understand how you've able, you've been able to get this range of both performance and cost you talked about. I thought I heard that you're optimizing the chips, you're using ObjectStore. You're, you've got an architecture that's not using SSD, it's using ObjectStore. So this, is their cashing there? I wonder if you could just give us some details of the architecture and tell us how you got to where you are. >> Right, so let me start off saying like, what are the kind of numbers we are talking about just to kind of be clear, like what the improvements are. So if you take the MySQL Database Service in HeatWave in Oracle Cloud and compare it with MySQL service in any other cloud, and if you look at smaller data sizes, say data sizes which are about half a terabyte or so, HeatWave is 400 times faster, 400 times faster. And as you get to... >> Sorry. Sorry to interrupt. What are you measuring there? Faster in terms of what? >> Latency. So we take TCP-H 22 queries, we run them on HeatWave, and we run the same queries on MySQL service on any other cloud, half a terabyte and the performance in terms of latency is 400 times faster in HeatWave. >> Thank you. Okay. >> If you go to a lot of other data sites, then the other data point of view, we're looking at say something like, 4 TB, there, we did two comparisons. One is with AWS Aurora, which is, as you said, they have taken MySQL. They have done a bunch of innovations over there and we are offering it as a premier service. So on 4 TB TPC-H, MySQL Database Service with HeatWave is 1100 times faster than Aurora. It is three times faster than the fastest shape of Redshift. So Redshift comes in different flavors some talking about dense compute too, right? And again, looking at the most recommended configuration from Redshift. So 1100 times faster that Aurora, three times faster than Redshift and at one third, the cost. So this where I just really want to point out that it is much faster and much cheaper. One third the cost. And then going back to the Gigaom report, there was a comparison done with Snowflake, Google BigQuery, Redshift, Azure Synapse. I wouldn't go into the numbers here but HeatWave was faster on both TPC-H as well as TPC-DS across all these products and cheaper compared to any of these products. So faster, cheaper on both the benchmarks across all these products. Now let's come to, like, what is the technology underneath? >> Great. >> So, basically there are three parts which you're going to see. One is, improve performance, very good scale, and improve a lower cost. So the first thing is that HeatWave has been optimized and, for the cloud. And when I say that, we talked about this a bit earlier. One is we are using the cheapest shapes which are available. We're using the cheapest services which are available without having to compromise the performance and then there is this machine learning-based automation. Now, underneath, in terms of the architecture of HeatWave there are basically, I would say, four key things. First is, HeatWave is an in-memory engine that a presentation which we have in memory is a hybrid columnar representation which is optimized for vector process. That's the first thing. And that's pretty table stakes these days for anyone who wants to do in-memory analytics except that it's hybrid columnar which is optimized for vector processing. So that's the first thing. The second thing which starts getting to be novel is that HeatWave has a massively parallel architecture which is enabled by a massively partitioned architecture. So we take the data, we read the data from MySQL into the memory of the HeatWave and we massively partition this data. So as we're reading the data, we're partitioning the data based on the workload, the sizes of these partitions is such that it fits in the cache of the underlying processor and then we're able to consume these partitions really, really fast. So that's the second bit which is like, massively parallel architecture enabled by massively partitioned architecture. Then the third thing is, that we have developed new state-of-art algorithms for distributed query processing. So for many of the workloads, we find that joints are the long pole in terms of the amount of time it takes. So we at Oracle have developed new algorithms for distributed joint processing and similarly for many other operators. And this is how we're being able to consume this data or process this data, which is in-memory really, really fast. And finally, and what we have, is that we have an eye for scalability and we have designed algorithms such that there's a lot of overlap between compute and communication, which means that as you're sending data across various nodes and there could be like, dozens of of nodes or 100s of nodes that they're able to overlap the computation time with the communication time and this is what gives us massive scalability in the cloud. >> Yeah, so, some hard core database techniques that you've brought to HeatWave, that's impressive. Thank you for that description. Let me ask you, just to go to quicker side. So, MySQL is open source, HeatWave is what? Is it like, open core? Is it open source? >> No, so, HeatWave is something which has been designed and optimized for the cloud. So it can't be open source. So any, it's not open service. >> It is a service. >> It is a service. That's correct. >> So it's a managed service that I pay Oracle to host for me. Okay. Got it. >> That's right. >> Okay, I wonder if you could talk about some of the use cases that you're seeing for HeatWave, any patterns that you're seeing with customers? >> Sure, so we've had the service, we had the HeatWave service in limited availability for almost 15 months and it's been about five months since we have gone G. And there's a very interesting trend of our customers we're seeing. The first one is, we are seeing many migrations from AWS specifically from Aurora. Similarly, we are seeing many migrations from Azure MySQL we're migrations from Google. And the number one reason customers are coming is because of ease of use. Because they have their databases currently siloed. As you were talking about some for optimized for transactional processing, some for analytics. Here, what customers find is that in a single database, they're able to get very good performance, they don't need to move the data around, they don't need to manage multiple databaes. So we are seeing many migrations from these services. And the number one reason is reduce complexity of ease of use. And the second one is, much better performance and reduced costs, right? So that's the first thing. We are very excited and delighted to see the number of migrations we're getting. The second thing which we're seeing is, initially, when we had the service announced, we were like, targeting really towards analytics. But now what are finding is, many of these customers, for instance, who have be running on Aurora, when they are moving from MySQL in HeatWave, they are finding that many of the OLTP queries as well, are seeing significant acceleration with the HeatWave. So now customers are moving their entire applications or, to HeatWave. So that's the second trend we're seeing. The third thing, and I think I kind of missed mentioning this earlier, one of the very key and unique value propositions we provide with the MySQL Database Service in HeatWave, is that we provide a mechanism where if customers have their data stored on premise they can still leverage the HeatWave service by enabling MySQL replication. So they can have their data on premise, they can replicate this data in the Oracle Cloud and then they can run analytics. So this deployment which we are calling the hybrid deployment is turning out to be very, very popular because there are customers, there are some customers who for various reasons, compliance or regulatory reasons cannot move the entire data to the cloud or migrate the data to the cloud completely. So this provides them a very good setup where they can continue to run their existing database and when it comes to getting benefits of HeatWave for query acceleration, they can set up this replication. >> And I can run that on anyone, any available server capacity or is there an appliance to facilitate that? >> No, this is just standard MySQL replication. So if a customer is running MySQL on premise they can just turn off this application. We have obviously enhanced it to support this inbound replication between on-premise and Oracle Cloud with something which can be enabled as long as the source and destination are both MySQL. >> Okay, so I want to come back to this sort of idea of the architecture a little bit. I mean, it's hard for me to go toe to toe with the, I'm not an engineer, but I'm going to try anyway. So you've talked about OLTP queries. I thought, I always thought HeatWave was optimized for analytics. But so, I want to push on this notion because people think of this the converged database, and what you're talking about here with HeatWave is sort of the Swiss army knife which is great 'cause you got a screwdriver and you got Phillips and a flathead and some scissors, maybe they're not as good. They're not as good necessarily as the purpose-built tool. But you're arguing that this is best of breed for OLTP and best of breed for analytics, both in terms of performance and cost. Am I getting that right or is this really a Swiss army knife where that flathead is really not as good as the big, long screwdriver that I have in my bag? >> Yes, so, you're getting it right but I did want to make a clarification. That HeatWave is definitely the accelerator for all your queries, all analytic queries and also for the long running complex transaction processing inquiries. So yes, HeatWave the uber query accelerator engine. However, when it comes to transaction processing in terms of your insert statements, delete statements, those are still all done and served by the MySQL database. So all, the transactions are still sent to the MySQL database and they're persistent there, it's the queries for which HeatWave is the accelerator. So what you said is correct. For all query acceleration, HeatWave is the engine. >> Makes sense. Okay, so if I'm a MySQL customer and I want to use HeatWave, what do I have to do? Do I have to make changes to my existing applications? You applied earlier that, no, it's just sort of plugs right in. But can you clarify that. >> Yes, there are absolutely no changes, which any MySQL or MySQL compatible application needs to make to take advantage of HeatWave. HeatWave is an in-memory accelerator and it's completely transparent to the application. So we have like, dozens and dozens of like, applications which have migrated to HeatWave, and they are seeing the same thing, similarly tools. So if you look at various tools which work for analytics like, Tableau, Looker, Oracle Analytics Cloud, all of them will work just seamlessly. And this is one of the reasons we had to do a lot of heavy lifting in the MySQL database itself. So the MySQL database engineering team was, has been very actively working on this. And one of the reasons is because we did the heavy lifting and we meet enhancements to the MySQL optimizer in the MySQL storage layer to do the integration of HeatWave in such a seamless manner. So there is absolutely no change which an application needs to make in order to leverage or benefit from HeatWave. >> You said earlier, Nipun, that you're seeing migrations from, I think you said Aurora and Google BigQuery, you might've said Redshift as well. Do you, what kind of tooling do you have to facilitate migrations? >> Right, now, there are multiple ways in which customers may want to do this, right? So the first tooling which we have is that customers, as I was talking about the replication or the inbound replication mechanism, customers can set up heat HeatWave in the Oracle Cloud and they can send the data, they can set up replication within their instances in their cloud and HeatWave. Second thing is we have various kinds of tools to like, facilitate the data migration in terms of like, fast ingestion sites. So there are a lot of such customers we are seeing who are kind of migrating and we have a plethora of like, tools and applications, in addition to like, setting up this inbound application, which is the most seamless way of getting customers started with HeatWave. >> So, I think you mentioned before, I have my notes, machine intelligence and machine learning. We've seen that with autonomous database it's a big, big deal obviously. How does HeatWave take advantage of machine intelligence and machine learning? >> Yeah, and I'm probably going to be talking more about this in the future, but what we have already is that HeatWave uses machine learning to intelligently automate many operations. So we know that when there's a service being offered in the cloud, our customers expect automation. And there're a lot of vendors and a lot of services which do a good job in automation. One of the places where we're going to be very unique is that HeatWave uses machine learning to automate many of these operations. And I'll give you one such example which is provisioning. Right now with HeatWave, when a customer wants to determine how many nodes are needed for running their workload, they don't need to make a guess. They invoke a provisioning advisor and this advisor uses machine learning to sample a very small percentage of the data. We're talking about, like, 0.1% sampling and it's able to predict the amount of memory with 95% accuracy, which this data is going to take. And based on that, it's able to make a prediction of how many servers are needed. So just a simple operation, the first step of provisioning, this is something which is done manually across, on any of the service, whereas at HeatWave, we have machine learning-based advisor. So this is an example of what we're doing. And in the future, we'll be offering many such innovations as a part of the MySQL Database and the HeatWave service. >> Well, I've got to say I was skeptic but I really appreciate it, you're, answering my questions. And, a lot of people when you made the acquisition and inherited MySQL, thought you were going to kill it because they thought it would be competitive to Oracle Database. I'm happy to see that you've invested and figured out a way to, hey, we can serve our community and continue to be the steward of MySQL. So Nipun, thanks very much for coming to the CUBE. Appreciate your time. >> Sure. Thank you so much for the time, Dave. I appreciate it. >> And thank you for watching everybody. This is Dave Vellante with another CUBE Conversation. We'll see you next time. (bright upbeat music)

(soothing music) >> Narrator: From around the globe, it's theCUBE. With digital coverage of IBM Think 2021. Brought to you by IBM. >> Welcome back to IBM Think 2021. This is theCUBE's continuous virtual in-depth coverage of the people, processes, and technologies that are changing our world. Right now we're going to talk about modernization and the Synergy with Cloud. And we're pleased to welcome Doug Armbrust, who's the VP GTS Cloud Synergy. Hey Doug, how you doing? >> Great, Dave. I'm excited to be on theCUBE, thanks for having me. >> It's our pleasure. Hey, let's talk a little bit of tech. What are some of the technologies that your clients are applying on their path to modernization? >> Sure. I'll give you three examples and three that we're seeing a lot of interest in from a services standpoint. One is automation. Automation is an area that's been a focus for... Several decades but... We're seeing a renewed excitement around the opportunity for automated operations. Really, I'll talk about two other technologies but the extension of automation and to some of the newer cloud technologies. So that's one. Two is cloud. Cloud has been a terminal industry for a while now and folks have been at various points of a journey to cloud-centric models and technologies. We're seeing an even accelerated transition to not just public cloud but also private cloud technologies, and in particular, need to interconnect those with one another and with a traditional environments. The last one, I think there's been a bit of a referendum on the technology over the last year is around containers, specifically Kubernetes, as a standard for that space. A cementing of direction around containers. Clearly, people are different stages of implementation and experimentation with the technology but I do see a referendum on this being a fundamental part of future technology and direction. >> So, okay. So automation, cloud, and containers. I'm going to ask you a follow up on containers because it's clear that when you look at all the data, it's off the charts in terms of adoption and ultimately our scenario is okay, it gets subsumed into the stack. But where... Where the customers ultimately want to go? Obviously, they're upskilling but what's the outcome that they're trying to achieve? >> Yeah, it's a good question. General question of the ask a modernization. I like modern things. We'd like to live in a modern house, my wife likes a farmhouse so guess where we live. (laughs loudly) We live in a farm house with... Modernized appliances and infrastructure. >> New cost to live with. (laughs loudly) >> Ultimately, enterprises, they're working back from an objective, and that objective, had this term digital transformation for about a decade. Underneath that umbrella, it's about being able to move and respond quickly. It's about being able to create innovation and accelerate innovation. I think probably most important is deliver on a customer experience and end customer experience. 10 years ago, what I expected when I went to a restaurant was a... If I could look them up on the internet and find their location, use my GPS, get there, I was good to go. I'm looking for... Use an app, them to remember my favorite place to sit. Very different expectations and that pressure on enterprise, to meet those annex and expectations is really at the heart of... The modernization and part of that's... Infrastructure modernization containers is interesting because it brings together, not just infrastructure, brings together how application development cycles are being implemented. It has implications for security that... Can be positive if done right. We do see that as... A key area to meet the end and business objectives. It's going to take some time. IDC, I think is the most bullish. They took like 80% of workloads. By 2023, we'll shift to containers. I believe that for newly created workloads. I think developers have got this in their hands and they understand the efficiencies for their own work as well as when this moves to production. This sort of DevSecOps model, kind of comes with containers if done right. There's a legacy that's going to be around a long time, helping customers understand those operating models and how to live with them both is going to be important over the next five to 10 years. >> You're talking about those drivers responsiveness, the innovation, et cetera. I live in an old house too and there's another component here which is that 80%, reasonable people could discuss that, because there's a risk component, right? I can modernize my house but I could jack up one into the house but it might mess up something that I just did. And so, CIO is obviously a risk-averse, they want to modernize but at the same time, they want to get from point a to point b with minimum disruption. To that end, I wonder if you could talk about what you saw during the pandemic. We're still in the pandemic but you had a reduction in budgets, virtually across the board, minus four, minus 5% in spending, had a shift toward work from home, whatever, VDI, laptops, rushed endpoint security, that whole thing. A lot of organizations try to do both. They said, "Hey, we're actually going to double down on digital transformation." We see this as a lean and opportunity. We got liquidity. How did COVID influence modernization initiatives in your client base? >> It impacted different clients in different ways. Some, as you mentioned, I almost view it as very Darwinian in the sense that those who had modernized and had capabilities, more deeply automated were ready for the transition that they had to go through so they were able to quickly shift to work from home. They were able to deliver on new client experiences, the analogy before in digital transformation, those pressures never went away, but COVID just brought new ones, and they expected all of those things but now they expected the restaurant... They expect the restaurant to bring that food to my door and do it in a safe manner. The challenges it brought on organizations were... In many cases, new. Some who were in a good position could accelerate work in place and leverage that. Others had a harder time, right? Those who couldn't translate technology to immediate returns, to kind of fuel that ongoing progress, had to make some hard decisions. I would say that's probably the single trend, projects are very carefully reviewed. There's that view of... "Will this help me now and into the future?" That's always present but it's present in a stronger manner than we would've have seen it for some time. In that envelope, can I come back to within those three technologies? Automation has certainly... We've seen a jump because of its nature. What we see in automation projects is... A faster time to implement and achieve some of the agility and flexibility that cloud provides but can take a longer timeframe if you haven't gotten far along in your cloud journey. Containers, even longer timeframe. So a lot of folks are looking at automation projects, particularly those that weren't as well positioned for sort of a quick turn and then taking that automation work and extending it into cloud and containers, as those initiatives progress. >> There are definitely some historical parallels and I could even go back to Y2K and look at all the application rationalization exercises that were going on back then. The technologies were different. You didn't have the modern cloud, containers have been around forever but not in the form of Kubernetes. The automation was scary back then but nonetheless, people were trying to use scripts or whatever they could do. But now, it's almost like an automation mandate, if you were in a digital business, you were out of business. So what are the... What are some of the learnings that you've seen from these modernization journeys that you're taking customers on that you might be able to share. >> Let me comment on automation first, I'll say it more generally. I think automation, you're right, we're not finding enterprises that are doing things manually. Everybody's gotten at least to kind of that scripting point. And then we see... That has its own journey. Then there's centralization and folks trusting the automation to enable self-service. That's sort of a... Kind of a tipping point to who is ready for COVID and who wasn't. Those who had hardened their automation to enable self-service generally could then call on that self service to meet the new demands that they were facing. The next stage and we see less folks there, we get into this sort of... Infrastructure as code. We talk about areas of intelligence in your automation. You talk about trust, not as many have progressed to where they trust their automation to... Proactively, maybe sometimes reactively respond to a situation or set of... You have to be very integrated at that point and you have to really believe in your automation. You then talk about integrating AI to sense, respond, make decisions and bring those back into your automation technologies. I'd say, that's still very future but folks are very intrigued by that. Your more general question, what's sort of some of the learnings. Really goes back to... Modernization needs to have a business school. That's become maybe more clear than it was a year and a half ago. In the absence of that, IT projects have always had some degree of failure. It's just the evidence of that failures, probably a little bit more poignant. Related to that, is there needs to be a strategic plan and in particular with modernization, it's easy to get caught up with the modern side. And Dave, you were kind of alluded to this before. If you're not thinking about the old, the connection to the legacy, that's a very common kind of failure signature. It's a marching ahead with the modernization, without a strategic plan and connect those things and an ability to kind of tackle a piece at a time. Sometimes budgets go away and that's a problem. Each step in the journey is really the third lesson. Needs to have incremental value. It needs to kind of pay back something to help fund the next stage of modernization. I'd say the last one and it's self-serving for us as a services company. It's helpful to have a partner on these journeys. In my particular area of focus, in a year and a half, we've had... 1,600 engagements. A lot of those engagements are people coming to us after making what they now view as mistakes. Some of the three areas I just mentioned. And being able to bring somebody in with experience with maybe some complimentary skills that can partner within an enterprise can be very helpful to avoid some of the pitfalls. >> I think, your point is right on. I've seen horror stories where people... Literally, we're going to go off the mainframe. They got decades old COBOL code that's working just fine and they literally risked their business trying to brute force migrate off and they never could... We're not going to freeze the code. It's just horror stories. But today's different, you can actually build an abstraction layer, leverage cloud services, and Kubernetes, and the like, use microservices to actually connect the old to the new. And that's the hardest part, again, old house analogies. I've done a lot of connecting the old to the new, that's the hardest part. You got to be really careful but today the technologies are enabling to do that and one of them is... Obviously, things like OpenShift. The definition of open, again, a little history here, it used to be... Unix was open and then Windows and then Linux, the LAMP stack. But really... That piece of your portfolio is a critical part to enable these types of moves. >> Absolutely. It's exciting that technologies are there and there's a path forward. And it's great to... Great to work with a partner, who's maybe, done that 10 or 15 times, or more and have them help guide you on that path. But the good news is there is... Enabling technologies to transform in a number of ways, depending on what the business objectives are for an enterprise. >> Cool. All right, Doug, we've got to go. Thanks so much for coming on theCUBE. It's great to see you. >> Okay, same Dave. >> All right. >> Appreciate it. >> Keep it right there everybody. This is Dave Vellante. You're watching IBM Think 2021. The virtual edition covered on theCUBE. (bouncy music)

>> Narrator: From theCUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hi, I'm Stu Miniman, the host of Cloud Native Insights. And when we kicked off this program, Cloud Native Insights, we wanted to talk about the innovation and agility that's happening, not just Cloud as a location. We're going to draw down a little bit into one of the very important pieces of a company and that's their websites and their applications, that live in that environment. And of course, that comes from a lot of changes over the years. Any of us that have been in tech for a couple of decades have worked from the early days, to of course today's multimedia globally distributed environment and everyone during the global pandemic, of course, has been (indistinct) straining their use of the internet. So really excited to welcome to the program the two co-founders of Netlify. I have Matt Biilmann, who is the CEO, and his co-founder Christian Bach, who is the president both of Netlify really the company behind Jamstack, which we're going to explain and talk about a bit. Matt and Chris, thank you so much for joining us. >> Thanks for having us. >> Thank you for having us >> All right so, let's start with just some of the basics. I expect that some of our audience is not familiar with Jamstack. You do a quick Google search and it's JavaScript, its APIs, its markup. And you say, okay, I understand what a bunch of that means. But, yeah, if you could give us kind of a compare contrast to what web development was before and how Jamstack's really helping to revolutionize what's happening in this space. >> Yes, so for many years, we built websites and web applications with an application based architecture, where every website or every application would be this monolithic application with typically like a load balancer, a set of web servers, application servers, and that database and every request through a page would go through this whole stack it would pass through the application layer, talk to the database, fetch template, merge data and template, build HTML on the fly and send it back to the user. And basically what we saw happening and what's been happening with the Jamstack is this decoupling of the actual front-end presentation layer of the websites and web applications and then the back-end layer. And the advantages there is that if you can really pre-build the front-end application layer, you can take the actual HTML, or an application shell and distribute it across a globally distributed network, you can get it into the hands of the user's browser very quickly. And then the back end, what we've seen happening there is that it's split up to all these different APIs and services you no longer have your one monolithic back end you have all these different services. Where some of your own but a lot of them are other people's services like Stripe or Twilio or Algolia or Contentful. So we've seen this shift to this architecture, where we're considered in a way that the stack has moved up a little from the old tooling where something like the LAMP stack would be common in really naming the programming language, the specific web server, the Linux server, the operating system, and so on right? And then up to a level where it's really about getting an application into the browser, using JavaScript as the runtime and talking to this whole new economy of APIs and services. >> Yeah, Chris I wonder if you could bring us inside your customers and the companies that you talk to. I think about for the longest time it was, maybe I just outsource my web development, but website is one of those key components that I share my value, I share what's going on, I want to be able to change it pretty often and there's so much more that I can do today than I could have done 10 years ago. We've watched that mark. So, help us understand, what skill sets do people need to have? what type of companies are using Jamstack? And, bring in if you can, Netlify. How is this a business and not just, an open source standards movement, that's helping to revolutionize what's happening? >> Absolutely, I mean, First of all, people using this and companies use this is extremely wide. Wide vertical, right? Its very horizontal. This is anyone with a digital property basically, right? I think what we've seen all the time is that, that we have a lot more channels than we used to have, right? So we started off just maybe having the one dot com, right? With limited functionality. And today, you have a multiple channels, right? You have the landing pages, you have the domains, you have lots of activities online. You have mobile apps and commerce is often a big part of it, and I would say especially the last few months, there's a lot of people that had the digital convergence points as one of many. And now it's the only ones, right? So I think it's become extremely important. I also think that when you look at your web infrastructure in general, it has been very complex, right? And you need a lot of different people, right? And you need to maintain staging environments, production lines, development environments. You need to, have a wide set of skills to maintain these things, right? And if a web developer wanted to do a lot of things, right? They have to go and tap DevOps and so on on the shoulder, right? And I think what the Jamstack is about saying, hey, you can get so much further as a web developer. Now, if you take the modern built tools, you can take the Git workflows, and you wrap around the browser that has become a full-fledged operating system and the API economy as Matt was just talking about. You have these workflows, or you potentially have these workflows, where you can get so much further, right? And that's very much Netlify submission. So Netlify saw this opportunity of decoupling the front end from the back end of the building from the hosting of creating an approach to making websites that would be many times faster, 'cause you have multiple points of origin and you don't feel fredurous. It's many times safer. There's not that huge surface area of attack. It's much more scalable, and so on. It was sort of a win-win-win. But the problem was, there was no viable workflow. If you take a traditional CDN, and you put it in, it doesn't matter really, if it's one or the other. As good as they (indistinct) services, they're all meant to sit in front of an origin, right? They're meant to buffer something. And if you have the gems, there's no origin in that way, right? The network in itself has to be an origin so it has to be architectured quite differently. And then there's a lot of things around CDCI and how you server lists and so on. That all had to be sort of re-merged . And Netlify is that glue, it is that platform that takes you from local development all the way out to edge nodes. But allows you to mix and match any tool. So it's not program independent. So you can say, well, we use a build tool, and that's PHP or Ruby or JavaScript, the react or Next or whatever it might be, right? And we use these APIs for this server, for this property. Over here we have a commerce site. Over here, we have a dotcom, that needs a huge enterprise CMS with tons of stakeholders. But the thing is that all of those now becomes something that plugs into your website. Rather than have to drive the website itself. And that's sort of frees up the silos. So when we see people using Netlify, we have companies using Netlify. Big Fitness Company, for example, that own fitness company that uses us for developer documentation, or their marketing sites, but also for their dotcom. But even if you go to the equipment that people have at home, and you log in, that's actually using some very nifty identity and remote based access control for Netlify and if you watch the video there, it's also going through a Netlify player, all right? We have fast food chains that has their dotcom and their marketing sites, but also the kiosks down in the store like the menus, the screens there. Rather than being an old Windows NT server running some .NET application in a dusty corner, why not have it like that? And so, both the category but also Netlify sort of brings in a solution and because it's decoupled from all those architectural choices, that means that you can now use the solution in a much, much wider setting. And we were sort of first to market doing this. They get serverless approach where you just push your serverless functions to get better Netlify. First Feature Deploy Previews Were invented by us and so on. So the Jamstack is an extremely wide fundamental architectural approach that matches basically anyone that wants to build web properties. Netlify is the segnostic wide platform that just makes it possible. >> Yeah, good Chris actually, I saw the Peloton use case up on the website and you're right, a very different experience rather than I bring my device, is it synced? Does it work with it? Really integrates those solutions. And you just brought up serverless, which is actually how I got connected to talk in Netlify. So, Matt, sorry, I think you wanted to jump in there but I was wondering if you could help us. I've looked at serverless and what the promise of serverless of course, is that I don't need to think about that underlying infrastructure. I just like developers build our applications. Well, feels like that's really the same mission that you have. And they're serverless is a piece of your story. So, maybe explain (indistinct) that out a little for us. >> Absolutely, I think it ties in, right? Basically, what we saw just from a architectural perspective was this approach of really decoupling front end and back end and so on and working in a new way that gave a lot of benefits to the inducers in performance and security and so on right? But on the other hand, early on, what we saw was that to adopt that approach, like developers had to deal with lot of different moving pieces like CICD, CDN. What to do about the API endpoints that didn't need to be dynamic, and so on. And as Netlify, what we saw was that we could give one intro and workflow for all of this and make it extremely easy for developers to work with this thing. And serverless plays a really important piece there, right? Because when Amazon pioneered AWS Lambda and took it to the world, right? I think the promise also for the front-end web developers of being able to simply write code and then not have to worry at all about where is it actually running? How are we scaling it? How are we operating it and so on, right? That's a really powerful promise, right? But at the same time, in the same way, what we saw earlier on was that for a front-end team to actually adopt serverless functions as part of the Jamstack, it introduced another level of complexity of now having to manage your serverless functions independent from your front end figuring out API Gateway endpoints for every one of them. And how about deployment pipeline for your functions layer versus deployment pipelines for the actual front end layer that's supposed to talk to those front ends. How about staging environments versus to production environments? How do you manage all that, right? So we saw that there was this inherent incredible potential, but also a lot of complexity, right? And as Netlify we saw that if we could give front end developers a web developers in general, an ene-to-end workflow, where they can work both with the front-end framework, write the code that will get deployed into the browser, but also just have a folder where they can write this serverless functions and then know that Netlify will take care of all of the wiring, right? When you open a pull request and get with new function we'll give you a URL on our globally distributed CDN where you can view both the whole front end, but also the function and sidestep sort of all of the complexities of linking together API Gateways, to functions of managing CICD pipelines and test environments and so on. And in the end, the serverless functions starts becoming a really important part of this Jamstack approach, right? Because you have this world where you have a front end that's often talking to many different APIs and services where again, some of your own and some other people's services. But really often you need some place to glue those together or to build your own custom API endpoint that talks to a couple of them and it has access to server site secrets and so on, right? And this idea of not having to suddenly operate and manage a whole set of servers and infrastructure just for that part of it, but simply just writing the code and then knowing, that you don't have to worry about the operation scalability or anything around that code. That's a really powerful paradigm. >> Yeah, that's one of the real challenges of the Cloud as you talk about the Paradox of Choice. There's so many ways to do things. Not necessarily... It's simple anybody... I was a blogger for many years and it was like, well, I'll just use the self-hosted WordPress, because I don't want to have to worry about that piece of it. Matt, I watched it you did a presentation talking about if I wanted to do WordPress hosted in a AWS that absolutely is not simple. I heard a podcast from one of your board members, Tom Preston Werner, talking about we need to be more opinionated. We need to be able to give more guidance to developers, maybe Chris if you could, how are we when the proliferation of choice, keeps increasing, making sure that people can... How do I make that decision tree? And how do we try to keep it simple? >> Absolutely, I mean, and I actually think that, that's a super relevant question, because you have a lot of choice as a web developer today. Front-end developers used to cut out Photoshop files and turn them into HTML, right? Now with the new advanced markup, and they have all these frameworks and flavors of JavaScript to choose between and there's these powerful build tools, And all those workflows and the browser can do everything you can imagine, right? And so yeah, there is a lot of choice out there, right? And I think, for Netlify what's extremely important is that we are opinionated in the right places. And so when it comes to, for example, a front-end tool and built tools and these things that web developers often face with having to choose between. Our role is to make it as simple as possible to use any of them. But also give you the opportunity of saying, well, this new paradigm allows you to actually mix and match, right? It allows you to use this tool for this property and this tool for this property and gives you a ton of flexibility. But still, come under one roof of a platform like Netlify. And I think that is very powerful. And so we also don't want to choose for you, we want to inform your choices and we want to make it as easy as possible to go and say, hey, these are my needs, what direction should I be going? And of course, we work with enterprise clients, so on migration services, and so on, right? And where we help them a lot with that. But if we locked down on a single flavor, or a single bill tool or a single front end framework, then we also limit the application of what we bring to market and we want to remain a little more open-ended there. But I think there's a lot complexity, a platform like Netlify is all about simplification. So all that wiring that Matt just mentioned, that at least goes, right? You don't spend hours configuring bondage caching and trying to find those edge cases, it just works. And that's a huge game changer for a lot of people, right? But there's definitely parts of the ecosystem that has a lot of choice. And we do our best to inform. And I think, under hand holding part, adjacent to that is the story of, well, do we then start using content management systems? Is this a whole new? Is it out with the old and in with the new? And I would say, you still have a lot of those needs, right? You still have non-technical people, for example, that needs to be able to update and create moves and content, and so on, right? And create content. And so you very often will need and an E-commerce solution or content management systems and so on. But what we're seeing there, is that we're speaking basically with every single major CMS out there. That are saying we're working on a headless system, or we already have a headless version, or we just gone full headless, that means that we work decoupled. So we don't no longer need to build the site. But we just provide like an independent source of content. And then it plugs into a platform like Netlify. So that can bring a lot of simplicity. And now you just have to maintain your content, but you don't have to worry about all the different environments and what is up to date and how does some of the infrastructure look like you press a button that commits to get a default preview, and it looks the same everywhere. >> I'm curious, what impact the current global pandemic has had on Netlify, and your customers. I saw you've got a COVID tracking project that you've done. But also now just there's different considerations when I think about what services I need to access from the web and what kind of connectivity the ultimate end user would have. So, what learnings have you had? What's involved there? >> In, obviously we, it depends a lot on, as Chris mentioned, right? The game circus is adopted horizontally across all kinds of areas and businesses and so on, right? So, we've of course seen businesses in sectors that are having a hard time and on the other hand, we've seen businesses and sectors that are exploding, right? We did immediately when the lockdown started happening and the pandemic started happening we set aside like a free plan for projects working in the space of tackling the information sharing around COVID and finding solutions and so on. And that was really interesting to see you mention the COVID tracking project, right? Which was a project like built a short time by small group of distributed incredibly talented front end developers and scientists and so on, right? And I think it was interesting to see that, how the Jamstack and our tooling and so on also really made it possible for them to build as a small distributed team the set of data information and tooling to a global audience, right? Seeing huge traffic peaks at time and just knowing that their architecture and our infrastructure could handle it for them. >> All right. Chris, I've got one, a little bit off to the side here. When I look at what Netlify is doing, you talk about having an open and independent web. And while we are fully supportive of that, we're a little concerned sometimes. If you look at what's happening across the globe, there's a lot of discussions. Will the internet actually fragment? Will certain countries wall off certain environments? Any concerns there? What do you look at? What are you hearing from your customers when you talk about that mission? >> It's one of the big challenges of all time, right? I think we all maybe took for given the Internet as the standard it became right? The way that you can publish without permission is pretty magnificent, right? And it would be indescribably painful for civilization if we lost that, right? And I think fragmentation is something that we all have to sort of worry around. From the way we see it, is that the web, the traditional monolithic approach, right? To which led to as a web that wasn't secure enough and wasn't scalable enough and wasn't performing enough and that's, for example, what opened the door for mobile applications, right? Where it just didn't make sense to pull in the UI every time you turn the page. So we ended up with a form that's it. We prebuilt the application, you download it, and then you speak to service for anything then atmosphere come up with it, right. And that makes perfect sense. That's basically the same architecture that we're bringing to the web a very large scale. Of course, the problem is that now there are gatekeepers there, right? There people, you have to ask for permission to publish and so on. And, and there are other attempts to say, "Hey, we need a performing web." And there's a very big players out there that say, "Let's come over and just..." Do we even need to call it the Internet? Can we just call it our company website? I'm not going to name any names here, right? But leading down, it's what we've called walled gardens, that are great for absolutely no one except for the company. And what we believe is that if you have a web that is secure and is scalable, and it's performant enough to justify at least the architecture maintaining and not having to run into any walled gardens and still say no, you don't need to use a handful of commercial platforms if you want to be heard rather than have your own web properties on your own custom domains, right? I think that's the part of the open independent viable web that we're fighting for. Basically, one that adopts and keeps adopting an architecture that is something that levels the playing field. And then they would also say, why Netlify? I mean, a few years before we started, like, try configuring your own CDN. And like that was reserved for the very, very large tech players. Now you can comment, you can literally click a button on Netlify, you get custom domain and ACS post process site that's globally distributed, automatically integrated into get. And that's on the premium plan. And so as a startup, you can level set together with everyone else and be available widely across the globe without performance issues, immediately. And so in that way, I'm also seeing that's a democrat sensation of performance, right? That means that, that's great. And for places where you see developing economies, where you often have brownouts, where you often can't depend on having viable services and is locally and so on, this idea of having he cover that and having something that's just automatically, you know what, don't even worry about it, because it's already ready to go in all these packets all around the world. That's a huge game changer. That's actually what we see a lot of adoption of the gems they can never find in those places as well. Guess that's just such a promise to the architecture. So, I hear what you're saying and I'm also very concerned about a fragmented web for political reasons as well across the globe. And from our angle, the way we fight for this is to make sure that it retains using an architecture that makes it accessible for me. >> Yeah, I heard many years ago, a friend of mine said, if you're a technologist it means that in general you are a technology optimist, which I definitely try to be. So, I love Chris how you've just brought in some of the potential opportunity Matt, I want to give you just... People out there they hear like oh, 5G is coming, it's going to completely change the world. Anything that you're seeing on your side as to real opportunities that we will see, just a step function in what your company is using. Jamstack, partnering with Netlify in your ecosystem. What are some of the early things that you see that are exciting you down the line for this? >> Part of it is simply like the whole ecosystem around the gem stalk growing up and the tooling, the APIs, the frameworks available around it, and the level of innovation that's triggered. And especially how it's triggering in... Especially how we're seeing like the potential for small, distributed teams to work together and build things with a global impact in a short time. And I remember a couple of years ago, we did a hackathon with together with freeCodeCamp. And of course, like since it was with freeCodeCamp, it was mostly like teams were mostly fairly new to programming and so on, right? It was pretty amazing to see what over a weekend with this architecture and with this tooling, with the vendors that were present there and helping out and so on, what the small teams could actually get done in a weekend, right? Like I remember the winning team had an app where the whole room would see an image on the main stage screen and then on their phone, try to place that image on the map and you would real time see how people ranked, how close they got and get a winner and so on, right? And that was all just from combining APIs and tooling, like history, like Netlify, like Honor Bee, like Google Maps, and so on, right? And I think, in some way we shouldn't forget just how much this kind of ecosystem of readily available APIs and services around this front end stake. It's allowing people to build things that years ago would have taken a very big team probably like a year to build, and suddenly you can have a relatively small group of relatively new programmers built something really impressive, right? So I think that's a trend we'll see continue accelerating And me and Chris are personally involved in advising and helping out a lot of these new startups in the space that are trying to bring new tooling to the world that makes more and more of these things possible and accessible. >> Well, Chris and Matt, I really appreciate you both joining such an exciting space. Talk about the cloud, agility and innovation, such a robust ecosystem. Thank you so much for joining. >> Thanks for having us. >> Thanks for having us. >> And I'm Stu Miniman. Thank you for joining and look forward to hearing more about your CUBE insight. (soft music)

>> Live from Seattle, Washington, it's theCUBE, covering KubeCon and CloudNativeCon North America 2018, brought to you by Red Hat, the Cloud Native Computing Foundation, and its ecosystem partners. >> Hello everyone, welcome back to the live Cube coverage here, three days at Seattle's KubeCon and CloudNativeCon. It's a conference put on by the Linux Foundation. Cube's been there from the beginning, breaking down all the action. 8,000 people, doubling attendance from the last one, now global, on a global scale, seen great traction in China and other areas around the world. It's about the cloud global. I'm John Furrier with Stu Miniman, our next guest, Kelsey Hightower with Google. Former code program share, now out in the wild on his own, super dope, playing with all kinds of new technology, it's great to see you, thanks for coming on. >> Proper you said the word dope, by the way, so congratulations there. I'm an attendee, I still have a keynote on Thursday but I do get to enjoy the floor like everyone else. >> So what's new, so you're now, again, there's a lot of pressure now every year. It's more and more people here, so it's a lot of pressure to kind of get all the action packed, but the growth has been pretty phenomenal. You've been looking at serverless, we saw some tweets, again you mention it's super dope, serverless is. You've got serverless, you've got a lot of stuff going on within the CNC app, you've got Kubernetes at the core. A lot of people like calling it the Kubernetes stack or the CNCF stack. Is it really a stack, is it really more of an operating model because there's stacks involved but how do you describe it, because this is a point of clarification. I mean, Kubernetes isn't necessarily a stack. Is it, how do people use it, what's the current state? >> I think when people say stack, you think about the LAMP stack, right? Linux, Apache, MySQL, it's a way of pre-packaging these ideas. This is something that worked for me, it may work for you, you say that enough times and then you say things like the Kubernetes stack. It's a quick, shorthand for Kubernetes and building on top of it. I think from the engineering perspective, when you look at Kubernetes and all the gaps that the CNC app is trying to fill these days, it's all this stuff you're probably building yourself, someone else is building it, and now we kind of have an outlet now. If you're working on a service mesh like list was, you have an outlet to give it to the rest of the world, open governance, and get some contributors. I think what we're seeing now is that hey, CNCF is kind of the place people go to figure out is someone building the thing that I've already started building and can I stop and just download that and go off? >> It's been very successful open source community, obviously, it's been end user leverage, it's been great and it's been open source, community led. Not so much vendor led, but vendors have been participating, so it's been great, but now as Kubernetes is going mainstream, the rise of Kubernetes is undeniable. No one can really deny that. Other end users are now coming in either to participate or to consume Kubernetes. How is that going in your mind? What's going on in the landscape, because people want multicloud, they want hybrid, they want choice. How are end users coming into the ecosystem to consume Kubernetes and the variety of goodness around it and what's going on there? Can you give some color around that option? >> I think regardless of the industry buzzwords like multicloud and hybrid and all that, Kubernetes is good on its own. It solves a lot of problems that your previous tools didn't solve, so people are gravitating towards it regardless in that direction. When you start to talk about portability, yes, it's nice to have two different environments and have the same tools work in a similar way between those environments, that's working well. The people that started three years ago that were doing it themselves, they're finding value and treating that as a service. We saw this happen to DNS, e-mail, so people are saying maybe the value isn't running it myself, so now you kind of see the vendor ecosystem understand what the value is. For a lot of the cloud providers, it's running Kubernetes, patching it, updating it, upgrading it, so that you can go focus on the other parts on top. That's where I think we are as an industry, and then there's gaps to fill, so that's where you see things like native, people building CI-CD tools on top, that's just where the new opportunities are so I think we've kind of matured. People kind of know what Kubernetes is, they know where their value line is for Kubernetes, now they're looking for their partners or vendors or community to just layer the new stuff on top. >> Kelsey, you bring up a great point there because understanding that line of what I should do myself and what I have to do versus what I can buy, consume as a service, is really tough for people, you know. I always say, ask IT departments, what do you really suck at? Because there's somebody else that probably does it better. A year ago, when I talked to users at this show, they were really downloading stuff, putting their things together, and when you asked them why, it was well, the Azure stuff hasn't matured. It just released, Amazon, I'm not sure where they're going with it. It feels like a lot has changed in the last year. You did Amazon the hard way a little over a year ago. What has changed over the last year, you know. >> We saw this with Linux, right? >> Are we ready for that, yeah. >> In Linux everyone use to build their own Linux distro, you took pride in it, using Gentoo and Slackware, and then you're like, I'm tired of that so you go get Red Hat or Ubuntu and call it good, and then you go focus on the other things. Naturally, Kubernetes is early project, has lots of gaps, you can fill those gaps by gluing together open source yourself, but now most of the managed services fill in the gaps by default. You click a button in GKE and a thing comes up, it's secure, has most of the pieces you need, it's integrated, you're like alright, I'm done with that part. >> The other thing, we talked a year ago. There's lots of companies here that are involved in Kubernetes. We've got over 70 that are compliant, and then you've got the service providers. From what I hear, it's people aren't trying to differentiate with Kubernetes and that's probably a good thing. It's something that's going to be baked into the platform, it's something you're going to consume with the other services that I offer, what do you say? >> If you make it different, then it won't work. >> Right. >> It'll be a different thing, so if you make it too different then you lose most of the benefits that we're all talking about here. The ability to learn a set of abstractions once, kind of like we did on Linux, if you start changing the system calls on Linux, then it's not Linux anymore, it's a different thing. >> Just to clarify though, if I'm running in one cloud that has their Kubernetes and I want to go to another, is it similar enough? Can I make that move? Do I need a vendor-independent version? >> So I think up to this value line I've run this container, ship the log somewhere, give me a way to secure access, that's pretty standard. Give me a load balancer. What isn't standard is how do I do CI-DC on top of that, that's not standard. There's different opinions on how to do that. If I'm in Google Cloud, we have IEM one way, Azure has IEM a different way, and same thing for Amazon. There's things around networking, security, that are going to be different based on the environment you're in. Same for on-prem, and that's where you start to look for help. If I go to Google, I'm going to use GKE maybe instead of running it myself on just a bunch of VMs, so that's where you kind of see that little divide. >> Is that going to be custom work, that's a great point, security for instance, we'll just pull that out there. Is that going to automate and be seamless or is that going to be a work area that's always going to have to be differentiated or coded or? >> So for example, we have the big vulnerability recently in Kubernetes world, right? >> It's a big CVE, it affected everyone running Kubernetes. That's a thing, as a vendor, for us GKE people, we upgraded automatically for them and said hey, there's a CVE, it's going to be really scary when you read about it but hey, you're patched. We've taken care of you, so I think people will still look for that relationship. Will it always be custom? At the app level, that is a different story. When you run your container and you want to access the things in your environment, so if you're in Google Cloud you may want to talk to Spanner, you're going to need an IEM set of credentials. That's a little out of scope of Kubernetes, so that's going to be integration work that the provider will do. >> So the holy trinity of computing industry has always been storage, network, and compute, and it changes certainly with cloud and all the goodness that comes out from serverless and whatnot, so containers is interesting. We always love containers but I've heard conversations recently where it's like hey, I want to treat containers not as a first class citizen because it doesn't meet my security boundary. I'm going to put a VM around that and run that under the covers with say, Lambda. Is that feasible, is than an option? I've heard talk about it, is anyone doing that? Is that an alternative, is this going to introduce new elements? >> Let's put it right, in Kubernetes by defaults we chose to build on top of Docker. Industry momentum, great developer workflow, but you're right, it made a security trade off. We know VMs are a much tighter security boundary that people are comfortable with. In that world, at that time, they were too slow for what we needed to happen. Thanks to Intel and others who pulled the thread of let's make VMs faster. Recently you heard the announcement of Firecracker, right, it's part of a derivative from the Chrome VM and that thing is optimized for these kinds of workloads, containers and serverless workloads. Now we go from 10, 20 seconds to hundred milliseconds. Now it makes sense to probably have this become an underlying thing. Now that we have the speed, maybe people say hey, we can maybe take the security without sacrificing the performance. >> That's the trade off. >> Pulled on the thread, you mentioned Firecracker. There's still this tension between what's happening in Kubernetes and serverless. We saw Knative is a hot topic point. It's probably natural that there's some tension there because it's like oh wait, why do you need to learn any of this stuff because if serverless will just make it as a service and make it easy and you don't need to learn all that container stuff and everything, what do you say? >> If you're a Kubernetes user, if you really think about the very broad definition of serverless, meaning I'm not managing the database, I'm using a managed database, serverless database. Storage, I'm using S3 or Google Cloud storage, serverless. Your load balancer, also serverless. So most people in the Kubernetes ecosystem, networking, serverless, storage, serverless, their database, serverless. The only thing that you can say isn't serverless is this compute component, everything else is. Now people are looking at serverless as this spectrum. How serverless are you? If you're on-prem and you buy a server and you rack it and install Kubernetes, you're less serverless, you're probably not serverless at all, no matter what you do. Now, if you put a lot of work in, you can probably put a serverless interface on top. This is what native is designed to do for people. Maybe you have an organization that supports multiple businesses inside of your org. They may not know anything about Kubernetes. You just tell them hey, put your code here, it will run, oh, that feels serverless. You can provide a serverless experience. The delta then becomes what can we do between a container and a function, so the foundation of my keynote is exactly that. What does it mean to take a container and put it into Lambda? What do you have to change? In my presentation, I don't even read write the code. There's a small shim between the two worlds because you're already using managed services around it. We're not talking about throwing away Kubernetes and then starting over our entire architecture. We're swapping out the compute layer. One is a subset of the other. Lambda is about events and functions, Kubernetes is about container and run it however you want. You want to run it when an event comes in, that's native. You want to run it as a batch job, run it as a job. You want to run it as a long running service, run it as a deployment, so that's all we're really talking about here. When we break it down, you're just talking about compute. >> You talk a lot about automation in the CI-CD areas, that differentiation where the value is. In a world as automation goes faster, what does Kubernetes look like when it becomes automated away? Because I don't want to manage anything, why even have managed Kubernetes? It should just automatically, you mentioned the patching. In an automated world, is Kubernetes just running under the covers, how does Kubernetes look down the road in your mind, in terms of when automation comes in? >> I've been in this game maybe over 15 years and one thing holds true: most developers want to focus on the business logic. We hire them because that's their skillset. When they check in code, it would be really nice if you can take it from there and get it where it needs to be. That's been the holy grail. We see it in mobile, you build an app, you put it on the App Store, Apple gets it to every device on the planet, done. Now it's the server side turn to do this. Whether you're doing serverless functions, Kubernetes, VMWare, or Linux, if you have CI-CD in front of any of that, the developer can still have the same experience. I check in code and you're picking a different deploy target. If you did that five years ago, and you understood it, and you were using, let's say maybe Mesos or just VMs, you bring in Kubernetes, you don't even have to change this part of the equation. This is why I tell most people, just focus on this endgame. My keynote last year was about this is the endgame because this is your coacher, this is your change management process, this is your discipline, and this is just a target where that compute goes. >> Alright, we've got two minutes left. I want to get your thoughts and share with the audience who's not here, a big waiting list, I know there's some lobby con going on all around Seattle, people flew in. Great place too to actually have some good lobby con meetings around the lobby area. So what's happening here, in your mind's eye, now you're not in the throes of all the events, you're kind of in the wild here with us, everyone else. What's the top story, what's going on, what's the vibe, what are you extracting out of all this activity as a top story, top level stories here? >> I think everyone's finding their place. If you're a security vendor, you kind of know where your line is, right? I've got this Twistlock shirt on. They want to plan a world where they need to integrate closer to the developer workflow, not just on the infrastructure side. If you're selling load balancers, service mesh is a thing, where do you fit in? The lines are getting a lot clearer. Kubernetes is starting to say maybe we should stop here. Maybe service measures should take it from here and that's where Istio comes in. Traditional vendors can now play in this well-defined space. On the storage side, what are you integrating? Now we have the storage interface, like the container storage interface. Now, if you're a net app, you know where you fit into the puzzle. You don't need to have your own Kubernetes distro. Two years ago, everyone was trying to come out with their own Kubernetes distro so they can actually have an anchor. Now you're like, ah, now I know where to play and now we also know what's missing. After years of doing this, people look back and say there's a lot of stuff missing. It's OK now to go create something new. >> It's a clear visibility into the landscape. What about the impact to end users? What is notable in your mind in terms of highlights, impact to end user organizations really going through this quote digital transformation, which is very cloud-based of course, but they're certainly changing and impacting, what's your thoughts on the end user? >> We're using some of the same words now. Forget the technology piece, now we can all start to talk about the same things, so when we say container, we kind of now are talking about the same thing. When we start to talk about sidecars, whether that's a service mesh, Envoy sidecar, or something that adapts your existing code to the new world, now that we're using the same language, we can actually talk. Traditional enterprise can talk to the startups and have a meaningful conversation. >> That's awesome, any other observations here in terms of the size of the show? Got a lot more activity, feels a little bit like re:Invent, I'm bumping into people, swimming through the crowds, the swag's hot. >> It's 8,000 people here and it feels like there's more users that know nothing about Kubernetes so even though we're about five years in, it reminds me of when we were just getting started. >> Lot more work to do but great, congratulations on all the work you've done Kelsey. Really appreciate you taking the time every year to come on theCUBE. We love having you on, great commentary, great keynotes, very entertaining. Thanks for coming on, appreciate it. >> Awesome, thank you. >> I'm John Furrier, Cube here with Kelsey Hightower telling us about all the breakdown of KubeCon, CloudNativeCon, the beginning of the cloud tsunami is happening, certainly changing businesses, changing open source, it's changing, it's on a global scale. We're here with coverage for three days. We'll be right back with more after this short break.

>> It's The Cube, covering AWS Summit New York 2018. Brought to you by Amazon Web Services and its ecosystem partners. >> Hey, welcome back everyone. This is The Cube's live coverage here in New York City with Amazon Web Services AWS Summit 2018. I'm here with Jeff Frick, I'm John Furrier. Our next guest is Sahir Azam, Senor Vice President of MongoDB for the Cloud products. Mongo's been very successful. Everyone knows it in the developer community. If you've done anything building Agile, Mongo's been there. Great to have you on. >> Happy to be here, thanks guys. >> So Mongo's been one of those success stories where, if you look at the LAMP stack days, and you now look at Agile, it's been the database for everybody. It's been scaling up nicely. Some people were saying, oh Mongo doesn't scale. Well, hello Cloud. You guys have done very, very well. Amazon's a big part of what you guys are doing. What's new with your business and The Cloud? >> It's been quite a story, to be quite honest. We were launched as an open source technology, just about 10 years ago, which was right around the time Amazon really came to market. So in many ways, we've always been well deployed, heavily used in The Cloud. If you look at the massive community phenomenon that is MongoDB, the majority of that actually sits in AWS. But the strategic sort of move that we made a couple years ago, based on customer input was, to start delivering MongoDB as a service, directly on Amazon Web Services. Now we're actually available in over 14 regions on AWS, and it's had a tremendous effect on our business. We launched it, obviously, with 0% of our revenue. It's now, two years later, 14% of our revenue, over 44 hundred customers, and it's just a rocket ship. >> It's such a great trajectory, but I want you to take a minute to explain the dynamics of the database market. Because clearly Amazon's always taking shots at Oracle, you get any chance it's always making fun of Oracle. Because you have the big old school database, but with IoT, databases are proliferating everywhere. And they're really critical part of Agile. How is the database landscape looking like, and how has Cloud taken it up a notch? How has it changed it? >> Yeah, definitely. I think there's sort of two angles I think we see that are really interesting. One is, I think the thing that always drove and still does drive the developer adoption among ODB, is the fact that it's much more natural for a developer to work in a document model. They think building an application, they're thinking about business objects. The user, an invoice, a product, and you can just map that so naturally as a developer in MongoDB, and that is just a much faster business innovation cycle than a traditional, relational database. And that will only grow as more and more organizations, even traditional organizations, start to build customer-facing applications, where their engineering teams now need to ship in an agile manner, pushing out new versions of their application weekly, or daily, instead of annually. So I think that's sort of fundamental. And in many ways, The Cloud accelerates that. Whether you look at the DevOps movement and what's happening there, we're seeing the shift where no one wants to spend the skillset and time to learn how to manage a distributed database system, or any database system, for that matter. They want to focus on writing compelling applications. So if we can deliver at a very economical price point and elastic service that then scales endlessly, it allow them to focus on their core business and us to focus on ours. >> And that's the benefit of The Cloud. But talk about this Atlas product, two years ago who had no customers. Now you have over 4,000 and growing. >> Correct. >> That's just plug and play off The Cloud? Order on the marketplace? How are the customers onboarding? >> There's multiple ways. We have certainly a very healthy self-service, direct-to-developer type of business, where they can go online, swipe a credit card, get started on our free tier, and start off with small development environments that are $10 a month, all the way through giant, globally distributed clusters that can scale an application to millions. So, that starts developer first. However, we're interestingly seeing an uptake of that, especially this year, even an enterprise, established, highly regulated accounts as well, where they have a massive Cloud migration happening in conjunction with Amazon, and they want to use MongoDB because the richness of our database. The ability to now buy through the marketplace and consume it as a service is really compelling. >> So you're curious about how your relationship with the customers changed when you went to as-a-service with the database. Was there significant change in that relationship? How does it change when you've got this ongoing, monthly billing activity? >> Definitely, great question. I think it changed interestingly. Obviously the financial model's different because it's a consumption based model, based on pay for what you use. So that's obviously very Cloud-centric, Cloud-native, that's more of the math side of things. What I think is more interesting is now, we're obviously managing the customer's mission-critical databases. So when they're buying into a technology like Atlas from us, or Stitch from us, it's no longer just choosing Mongo because it's a great product. Its' choosing Mongo because it's a company they trust to run a mission-critical application and scale it as a partner. So it's elevated the strategic nature of how we're used, as a modern, persistent store and database. As an alternative to Oracle is sort of one angle, but now to look at it as a trusted partner. Because frankly, there's a share of risk model that has to happen in a Cloud services model. And that's been the biggest dynamic that's elevated our standing in many of these accounts. >> I presume you see an increased trajectory. It's going to take an increasing share of your total business as you go forward. >> It was 14% last quarter, certainly it's a big focus of ours. It's growing over 400% per year from a scale point of view. So we're doubling down, no question. >> Take a minute to talk about MongoDB Stitch and the four components you guys have in there. What's relevant about that? Why is it important for MongoDB customers and potential customers? >> At the macro level, we're seeing the constant trend of developers wanting to be more productive and consume higher levels of abstractions, and they have to write less code. That's the macro reason why we built Stitch. Because it's always been our mission as a company, to empower developers and build great, amazing apps. But at a specific level, what's interesting is, now that we're in The Cloud, we can enable interesting functionality in a few ways. In one sense, many developers, many engineers, have been used to things like triggers in the relational world, meaning, you're watching for data changing and you want to execute some sort of action. So now we've brought triggers into the non-relational modern database world, which Stitch triggers. So now any change in a database in Atlas can trigger an integration into Amazon's Kinesis service, or dumping data into S3, a variety of different use cases, to enable real time, sort of reactive application. So that's sort of fundamental, that's number one. The second is, enabling client-side apps. Mobile applications, rich web applications, to have more enabling, faster technology. Because now the client app can interact with the database in a much richer way, with the secure model. The query anywhere service does exactly that. It brings the full power of Mongo all the way through the edge, all the way through the client-side application, with Mongo Mobile. So we're really extending our reach and architecture because fundamentally, what we're hearing from developers is, we want to work with MongoDB because it's the best way to work with modern data, but help me do that everywhere. >> It's like stitching together all the data. Jeff, we were just talking about on the IoT portion of our intro package, how, if you stitch it all together, you can really bring everything beautifully together. Because the operators are spending a lot of time wasted on brunt work and tasks that they don't want to do. And with The Cloud, I think this is one of the value propositions we're seeing this year become very clear. And sort of with the VMware relationship annoucement a couple years ago, you're going to hear about it at Google Next and some other Cloud conferences. The developers are king. The operator's still going to be an elevated role, they're not going away. The storage administrator becomes the IT Operations guy, so the operators and the developers are going to create a nice, symbiotic relationship. Is this is where Stitch hits home? >> It his home from a governance and security standpoint around that, as does Atlas, right? Because what we're seeing is the modern operators are saying, listen, it's not strategic for us to learn all the bits and bites of infrastructure management anymore, or database configuration management, whatever it might be. But it is strategic to say, what are the key services that we're going to partner with for the long term of this business, while protecting governance and risk, thinking about security, abstracting away any particular providers. We're definitely seeing an evolution in the traditional operations role, and then at the same time, a developer's influence is consistently increasing in the market. >> I want to get your thoughts on this. You've been an industry veteran for a while, going back to the old BMC days, or before that, looking at the early days, and when the tech stacks are pretty well understood. And certainly Mongo made their bones, early days with LAMP stack, early days with Open source, now certainly changed with Cloud. Looking back now and seeing what's happening now, a lot of people are reawakening to The Cloud. I was just talking to an investor in Silicon Valley, who was doing some work in China just five years, has kind of been out of the enterprise IT space, he's like, damn, the stack has changed significantly. What have you observed, how would you talk about the changes between just five, six years ago and today? From a stack standpoint, from a capability standpoint, from a critical architecture standpoint, what's your view? >> I think, first and foremost, we're seeing a shift in application architecture. We're seeing the idea of micro services, decomposed applications, decoupled components and functionality, that's only rising. And we're seeing that, interestingly, not only for new applications, but also legacy modernization of existing applications. So now, that's actually driving a change in our business. Instead of the shiny, new IoT apps or mobile apps or web apps, that Mongo's always been strong for, we're now seeing 30% of our business come from legacy application modernization to micro services. >> 30% of your business is modernizing legacy apps? >> Correct. >> Wow. >> As they want to drive faster developer productivity, better economics, obviously, of running that application and build it on a more modern platform and architecture. >> You put a container around Kubernetes, you can now bring them into a modern architecture without sunsetting them rapidly. You don't have to rip and replace. You can just let it take a natural lifecyle. >> Right. And we basically play with that in two ways. If you're in the public Cloud, there's a nice fit between Kubernetes wrapping all the different app components, making them abstracted, scalable, Atlas underneath this fluid data layer. Or, if a customer's their own data center trying to modernize their stack, standardizing on Kubernetes, we now integrate our IP around automation and management directly into Kubernetes. That was one of the big announcements we made a few weeks ago. >> That makes Mongo really more versatile than ever before. I think the database as a service proves that you can really see the value of how having not a one spot only in the stack you can sit down with Atlas and then provide agility. Is that what's going on? >> The key driver is always agility for us. And then there's, oh wow, there's a huge cost savings to this as well. Whether it be in terms of productivity, infrastructure cost, just because of the native architecture, so as we see more and more organization become software companies, effectively, as the saying goes, that's just been a huge tailwind to our business. >> So two final questions for me, and I'll Jeff ask his questions. One, what's the relationship with Amazon look like now? And the second question is, what should people know about Mongo if they haven't been keeping in touch with Mongo lately? What's the new, big bumper sticker that they should know about from Mongo? >> On the first point, the relationship with Amazon is very strong. We obviously partnered with them originally when we built Atlas and continued to do so. And just core architecture. Building a database and service that's best in class on their platform. And expanding initially from four or five regions to now global footprint and that was the first phase. Now, we're heavily focused on going to market. Whether it's our sales teams working together on accounts, working on migration opportunities, or new application architectures. Whether it's marketplace adoption that we're together, trying to drive in inquiries. There's quite a bit of collaboration happening. Certainly they have databases and services, but we believe certainly functionality-wise, there's a huge ecosystem around Mongo, and they see that and want to empower them with Atlas. So that's been a huge advantage to driving growth into the market. The second point around what I would want people to know about Mongo is, MongoDB today probably would surprise people from our original roots. Our original roots were systems of engagement, high scale web applications, new apps, we're fantastic at that. Obviously, Stitch is a way to double down on that value. But as I touched upon earlier, now we're really betting on a more general purpose strategy, where we brought forth things like transactions and acts of compliance for the first time to non-relational databases. So we really believe that there's no application today for which Mongo can't give the same level of developer benefit. Even if it's a heavy transactional mission-critical application. >> Doubling down on the web app, core business, giving them more range and functionality to go anywhere they want to go with those apps. >> Exactly. And, saying alright, there's this huge wave of billions of dollars built on legacy technology, how do we unlock those applications, get them on a modern platform, that allows those apps to stick around for the next 20 years and deliver customer values. >> It's not your dad's tingen, I guess that's the take away. >> Inside joke, tingen. Formerly MongoDB. Thanks for coming on The Cube. Great to see you. Congratulations on your role at Mongo. Great company, CMO. Great to see your success, thanks for coming on. >> Thanks for having me, I really enjoyed the conversation. >> The Cube, here live in New York City. More coverage, stay with us. I'm John Furrier with Jeff Frick. We'll be right back, thanks for watching, stay with us.

>> Announcer: Live from the Computer History Museum in Mountain View, California. It's theCUBE covering DevNet Create, 2018, brought to you by Cisco. (techy music playing) >> Okay, welcome back, everyone. We're live here in Mountain View, California, in the heart of Silicon Valley for Cisco's DevNet Create. This is their new developer outreach kind of cloud, devops conference, different than DevNet their core, Cisco Networking Developer Conference is kind of an extension, kind of forging new ground. Of course theCUBE's covering, we love devops, we love cloud. I'm John Furrier with Lauren Cooney, my cohost today. Our next guest is Alex Ellis, project founder of OpenFaas, F-A-A-S, function as a service. That's serverless, that's Kubernetes, that's container madness. You name it, that's the cool, important trend, thanks for joining us. >> Yeah, thanks for having me, it's great to be here. >> So, talk about the founding of the project. So, you're the founder of the project-- >> Alex: Yeah. >> And you now work for VmWare, so let's just get this-- >> Yeah. >> On the record, so-- >> Alex: Yeah, I think this is-- >> Take a minute to explain. >> This is important just to set a bit of context now. I started this project from the lens of working with AWS Lambda as a Docker captain. I was writing these Alexa skills and I found that I had to hack in a web editor and click upload, or I had to write a zip file, put dependencies on my laptop, and upload that to the cloud every time I changed it. It just didn't feel right because I was so bought into containers. It's the same everywhere, there's no more, "It works on my machine." >> John: You're going backwards. >> Right? (laughing) So, I put a POC together for Docker Swarm and nobody had done it at that point, and it got really popular. I got to Docker Concourse Hacks Contest and presented to 4,000 people in the closing keynote, and I kind of thought it would just blossom overnight, it would explode, but it didn't happen, and actually, the months... We're going back 14 now, I grew a community and spent most of my time growing the community and extending the project. Now, that has been really fruitful. It's led to over 11,000 stars on GitHub, 91 individual contributors, and much, much more. It's been a really rich experience, but at the same time-- >> So, rather than going big rocket ship you kind of went, hunkered down and got a kernel of core people together. >> Alex: Yeah. >> Kind of set the DNA, what is the DNA of this project if you had to describe it? >> Yeah, so I think at the heart of it it's serverless functions made simple for Docker and Kubernetes. >> Great, and so how does Amazon play into this? You were using Amazon cloud? >> Yeah, I was using AWS and I was using Lambda, and that flow was not what I was used to in the enterprise. It wasn't what I was used to as a Docker captain. You know, I wanted a finite image that I could scan for vulnerabilities. >> John: Yeah. >> I could check off and promote through an environment. >> John: Yeah. >> Couldn't do it, so that was what OpenFaas aimed to do, was to make those serverless functions easy with Docker as a runtime. >> Well, congratulations, it's a lot of hard work. First, building a community's very difficult, and certainly one that's relevant. Cool and relevant, I would say, is serverless and functions. We'll certainly be seeing that now at the uptake. Still early on, but people are working on it. So, then now, let's forward to today. You work for VMWare, so-- >> Alex: Yeah. >> How did they get involved, are you shipping the project to VMWare, do they own it? Do you maintain the independence? What's the relationship between VMWare, yourself, and the project, if you can talk about that. >> Yeah, I think that's a great question. So, I got to the point where I had demands on my time around the clock. I couldn't rest, open source project, weekends, nights, the lot. >> John: You need the beer money, too, by the way. >> Right, yeah. >> You need some beer money. >> And I was working at ADP and just doing all of this in my own time, and then had a number of different options that came up and people saying, "Look, how are you going to sustain this, "how are you going to keep doing what you love?" You know, you should be working on it full time. One of the options that came up was from VMWare to work in the Open Source Technology Center. It's relatively new-- >> John: Mm-hmm. >> And the mission of the OSTC is to show VMWare as a good citizen in the community and to contribute back to meaningful projects, right, that relate to their products. >> Yeah, and they have good leadership, too, at VMWare. A lot of people don't know that. We did a couple CUBE interviews with them last year, and there is a group inside VMWare that just does that, not with the tentacles of VMWare and Dell Technologies in there. It's an independent group. >> Alex: Yeah. >> They probably go to some meetings and do some debrief, but for the most part it's kind of decoupled from VMWare, right. >> Yeah, right. So, the mission is not necessarily to make money and to produce products. It's to contribute to open source. Help with inbound so when we need to consume a project in a product, and outbound when we want to make the world a better place. >> So, I'm not going to put words in VMWare's mouth, but I will speculate covering VMWare since theCUBE started. We've been to every VMWorld and everyone knows we've got the good presence there, but if I'm VMWare I'm like, "Hey, you know what, we just "did a deal with Amazon, our enterprise "group is not so cloud savvy." I mean, the enterprise, there are operators, not true cloud native, but they're bridging that gap. The world of cloud native and enterprise is coming together. Does this project fit into that spot? Is that kind of where they saw it? Did I get that right or what was their interest other than doing-- >> Alex: Yeah. >> Helping the world out and solving world peace in the open source community. >> Yeah, so the mission of OSTC is slightly different. It's to contribute back to meaningful projects and to have this presence in the community. You know, I think OpenFaas is particularly attractive because it has such a broad community. There's people all around the world that are contributing to it, very active. For VMWare it makes a lot of sense because it runs natively on Kubernetes or Docker Swarm, and it's gained a lot of traction, people are using it. >> John: Mm-hmm. >> I had a call with BT Research before I came out and they said, "We've been using it for seven months. "We absolutely love it, it's transforming "how we're doing our microservices," and so I think that's part of it, as well as already have kind of a lead. Already have a lot of momentum with this project. >> So, are you looking to, you know, I know that the organization that you work for is really focused on driving this outbound, right? >> Alex: Yeah, yeah. >> Is VMWare using this internally as well? >> So, I think there's been a number of people who've shown an interest. You can think, "Right, there's a problem "we could solve with this," and I'm just getting my feet under the table, but really my mission is to make serverless functions simple to build this community-- >> Lauren: Mm-hmm. >> And to have something that people can turn to as an alternative. So, one of the things that I did in the talk yesterday was, "How do you explain OpenFaas to your boss," and one of the points there was to unlock your data. >> Lauren: Mm-hmm. >> And I think we talked about this briefly before, now with controversies recently about data and who owns it, what's happening with it, I think it's even more relevant that-- >> John: Yeah. >> You can have full control over the whole stack if you want-- >> John: Yeah. >> Or use a product like Microsoft AKS, their Kubernetes service-- >> Lauren: Mm-hmm. >> Or GKE and actually treat OpenFaas like a very thin layer of automation. >> Lauren: Really, okay. >> Or go full stack and have everything under your control. >> I mean, that's a great conversation to have, too, because obviously you're kind of referring to the Facebook situation. Zuckerberg's testifying it front of Senate yesterday, Congress today, and it's funny because watching him talk to senators in the US, they really don't know how stuff works, and so if you think about what Facebook does... I mean, granted they took some liberties. They're not the perfect citizen, they got slapped. They took it to the woodshed, if you will, but their mission is to use the data, and this is where cloud native's interesting and I think I want to get your reaction to this, you need to use the data, not treat it as a siloed, fenced in data warehouse. That model's old, right-- >> Alex: Yeah. >> It's now horizontal and scalable. Data's got to move and you've got to have data to make other things happen. That's the way these services are working. >> Yeah. >> So, it's really important to have addressability of the data and you know, GDPR takes an attempt at, you know, kind of hand waving that simple argument away. I'm not really a big fan of that, personally, but the role of data's super important. You've got to make it pervasive, so the challenge is how do you manage those controls. Is that an opportunity for functions? What's your reaction to that whole paradigm of data? >> Yeah, so we're talking about anonymous usage data, like Facebook situation or-- >> Just data in general... Oh, no, just data in general, if I'm an application and I have data-- >> Alex: Yeah. >> That I'm generating, same development of service-- >> Alex: Yeah. >> I need, you might want to leverage that data. So, I'm going to have to have a mechanism for you to share that data to make your service better-- >> Alex: Yeah. >> Because data makes data, you know-- >> Alex: Yeah. >> The alchemy side of it is interesting, but then there's all... You get trapped in regulation, licensing, it can be destructive. >> Yes, so as an engineer, and as an open source engineer, you find people that have no clue about what an MIT license is to a GPL or why you'd use one or the other. I think there's a lot we can do to educate the wider community and help them to learn the basics of these issues. When I was at university we had a course on ethics and legal issues and licensing, and I heard on the radio earlier on the Uber that they're starting to try and up the level of that again, and I think it really needs to start at a ground level. We need to educate people about these issues so that they're aware of how to handle the data. I mean, if you look at common tools like Docker and VS Code and Atom, popular editors, they collect anonymous usage statistics and you have to opt out. You know, should OpenFaas collect data as well, because it can be super helpful for us to know the right thing to do. >> Yeah. >> And when you come to open source you get no feedback until somebody wants support from you and it has to be done yesterday for free. >> Yeah, yeah, yeah. >> And so, yeah, getting data can be super powerful. >> Well, Alex, you bring up a great point. I think this is something that's worthy of an ongoing conversation. I think it will be, too, because GPL, Apache license, all these licenses were built when open source was a Tier 2 citizen, so the whole idea of these-- >> Alex: Yeah. >> Licenses was to create a robust sharing economy of code, and you know, with the certain nuances of those licenses. But just like stacks get updated and modernized with what we've seen the containers and now Kubernetes is serverless, the stack is changing and modernizing. The licenses have to, as well, so I think this is something that... I don't, I think it's kind of like we've got to get on it. (laughing) It's like I think we should just, this is a work area. It's not necessarily... It's game changing if you don't do it, right, because it could-- >> Yeah. >> It could flip it either way. So, to me that's my opinion. >> Well, I think you're under MIT, correct, is that-- >> So, it's under MIT right now. >> Lauren: Okay. >> One of the things that I didn't realize when I started the project is if you want to get into a big foundation like the Cloud Native Computing Foundation you need an Apache 2.0 license, and the main difference is that it offers some protections around patent claims, but it's basically-- >> Lauren: Okay. >> Compatible, so it is a minefield, and it's-- >> Lauren: So, that's just for the CNCF? >> Right, and the Apache Foundation, obviously as well. >> Lauren: Yes. >> And probably many others follow suit because I think it, we talk about the-- >> John: It's the dual source, it's the dual source. >> A refresh... >> John: Yeah, yeah. >> Right, it's a compatible license, it seems to help a lot of people. >> Lauren: Mm-hmm. >> That's a huge issue because you could be well down the road with committing code and then the lawyers will make you take it out. >> Right, so that's why organizations like the Open Source Program Office exist within VMWare, to help these issues and to monitor and do compliance. They may use software like Black Duck to check stuff-- >> Lauren: Yep, mm-hmm. >> Automatically because you don't want to be doing checks on your aircraft once it's in the air. >> Lauren: Mm-hmm. >> John: Yeah. >> You want to sort out everything out on the ground. >> You'll be grounding your fleet, that's for sure-- >> Right. >> When it comes to that, how do you handle that with licensing? How do you guys handle that when people contribute? >> Yeah. >> Are they aware of the license or they don't understand the implications? >> So, with OpenFaas we follow a model very similar to the Linux kernel, which is a sign off developer certificate of origin. What you're saying is I'm allowed to give you this code, I'm allowed for this to be a part of the project and I wrote it, I originated it. >> Lauren: Mm-hmm. >> And that's pretty much a good balance between a full contributor license agreement and nothing at all. >> John: Yeah. >> Lauren: Mm-hmm. >> But look, there's a lot of projects in this space right now. I don't know if you've noticed that, Kubernetes serverless projects. >> Yeah, I mean, it's a lot of really interesting, it's why I like this show here. I think what Cisco's smart to do here at DevNet Create is identify the network programmability, which really takes devops, expands the aperture of what devops is, so-- >> Alex: Yeah. >> You know, as you got new applications coming online some developers want nothing to do with the infrastructure. Kubernetes has got a much more active and more prominent role with layer seven primitives, for instance, or-- >> Alex: Yeah. >> Managing things down to the network layer. You're talking about policy services inside services on the fly, so this is really a big, a good thing, in my opinion. So, you know, I think, Kubernetes, most people look at as a kind of generic orchestration, but I think there's so much more there. >> Alex: Yeah. >> I think that to me is attracting some really rockstar developers. >> Yeah, well I think, you know, the fact that you are open, you're under the MIT license, which I am a fan of-- >> Alex: Yeah. >> And you know, it is, you're on a very successful trajectory in terms of, you know, what you're building and who's engaged and the fact that VMWare is behind you means that they're going to put some money into it, hopefully, and help you guys along as it works, but it is also a project that is not... You know, it doesn't have folks just from VMWare. >> Alex: Yeah. >> It's really, really diverse in terms of who's committing the code. So, I think there's a lot of things that are really going for you. Now, who do you see, you mentioned competitors... >> Alex: Yeah. >> So, can you talk a little bit about what the ecosystem there looks like? >> Yeah, so there's a number of projects that I think have made some really good decisions about their architecture and their implementation. They all vary quite subtly, and one of the questions I get asked a lot is, you know, how is this different from X, cubeless nucleo, and if you look at the CNCF landscape there used to be a very small section with OpenFaas, Lambda, and a couple of others. It's now so big it has its own PDF just about serverless, and I think that's super confusing for people. So, part of what we're trying to do is make that simple and say, "Look, there may be many options. "Here's OpenFaas, here's how it works. "You can get it deployed in 60 seconds. "You can have any binary or any programming language "you want and it will scale up over Kubernetes." We'll just make a really deep integration, give you everything you'd expect, really nice developer experience. >> Lauren: That's great. >> What are some of the use cases you see right now, low hanging fruit for developers that want to come in and get involved in the project? Have you guys identified any low hanging fruit use cases? >> So, what I've seen, and I talked about this a bit yesterday in the talk, is three big use cases, really. The first one was Anisha Keshavan at University of Washington. >> Lauren: Mm-hmm. >> Now, she's doing a lot of data science with neuroinformatics, medical images. She's able to take scans of brains and give them to people like you and me, who don't know anything about medical science. We just draw around the lesions and we train her model, and then she makes it competitive like a game, gamefies it, you get more points, but actually, what we're doing is making the world a better place by training her medical imaging database. >> Lauren: Mm-hmm. >> She'll then use that as an OpenFaas function to test real images as part of her postdoctorate. >> So, she's crowd sourcing, wisdom of crowds. >> Alex: Right. >> Collect some intelligence for her research. >> Now, one of the other things that I think's really cool is in the community we built out a project with two 17 year olds. Two 17 year olds built a really cool project, and when I think back to when I was 15, 16, I was playing with something like PHP on Windows Lamp Stack. You know, I had to do everything myself. >> John: Yeah. >> They got, like, this scaffolding built up and they could just go to the tenth story and just keep adding on. >> John: Yeah, yeah. >> And they didn't have to worry about managing this infrastructure at all. >> Or architecture, foundation architecture. >> Alex: Right, right. >> Yeah, and that's exactly the reason why you want to do that. >> So, they wrote some small blocks of Python that we found this machine learning code that could convert a black and white image to color, wrapped it in a box and said, "There's a function," then dropped it into OpenFaas and started feeding tweets in, and that was pretty much it. >> John: Yeah. >> Now we have @ColorizeBot, a bit of a strange spelling but you'll find it on Twitter, and it's been in Le Monde newspaper, all round the world. It was pronounced at CubeCon as well, and it's just a super interesting way of showing how you can take something very complex, right, and democratize it. >> Yeah, we'd love to get those people working for theCUBE and put the little cube box and throw all the tweets in there. >> Alex: Right, yeah. >> Alex, thanks for coming on, congratulations. What's next on your project, tell us what's going on, what's next for you, what are you guys conquering next? >> So, I'm really focused on growing the team and community. We've got an open recruitment position open right now and a small team that's building internally. I think the more people we can get contributing on a regular basis the more support there's going to be for the community, the more people are going to want to use this Actually had 26 people join a call last week. "How to contribute to OpenFaas," that was the name of it. >> Lauren: Mm-hmm. >> Around the world, and the best part for me was where we got to the testimonies and I had people just sharing their tips and experiences. How rewarding it is to contribute something bigger, something that you as a developer will actually want to use. >> Yeah, and the value opportunities, to extract value out of the group-- >> Yeah. >> It's phenomenal, functions as a service. Super relevant in cloud and devops as the middleware, if you want to call it that, expands more capabilities in devops are coming. It's theCUBE coverage here at DevNet Create. We'll be back with more live coverage here in Silicon Valley in Mountain View, California, after this short break. (techy music playing)

>> Announcer: Live from Barcelona, Spain, it's theCUBE, covering Cisco Live 2018, brought to you by Cisco, Veen and theCUBE's ecosystem partners. (upbeat electronic music) >> Hey, welcome back, everyone, to our live coverage from theCUBE here in Barcelona, Spain, for exclusive coverage of Cisco Live 2018 in Europe. I'm John Furrier, cofounder and cohost of theCUBE, with my cohost this week, Stu Miniman. Been to many events also, senior analyst at wikibon.com. Stu and I have been breaking down all the action here in the DevNet zone. And we have with us here as our guest, Ashley Roach, who is a principal engineer and evangelist with Cisco. DevNet himself, has full view of what's going on. Welcome to theCUBE. >> Hey, thanks for having me. Appreciate it. >> Good to see you again. We covered DevNet Create, which was really our first foray into what DevNet was doing outside of the Cisco ecosystem, bringing that cloud-native developer into the Cisco fold. Here, it's the Cisco show where all the Cisco ecosystem and your customers are growing into the cloud and programming with DevNet. So congratulations, it's been phenomenal. It's been one of the top stories we've been covering as DevNet has just been explosive. >> Oh, thanks a lot. It's been a lot of hard work. >> People have been learning, they're coding, they're being inspired, and they're connecting, It's a very sharing culture. Props to you guys and the team. Well done. >> Ashley: Appreciate it. >> So what is DevNet? I mean, this is a cultural shift. We've been reporting on theCUBE all year and last year. But really this year, end of last year, we started really putting the stake in the ground saying we are going to see a renaissance in software development. Linux foundations, reporting that there's going to be exponential growth in code and open-source. You seeing that you can create intellectual property with only 10% of the energy codewise, 90% using open-source. They call that the code sandwich. Again, this is just data that they're sharing, but it points to the bigger trend. Developers are becoming the important part of the equation, and the integration of the stack from network to application, are working together. And again, proof point's there, things like Kubernetes, containers, have obviously been out there for a long time. You're starting to see the visibility for developers. >> Right. >> John: You're at Cisco, you're in the middle of all this. You're seeing one side of the camp and the other. >> Ashley: Yeah. >> What's your view? >> Yeah, I think that's a good, it captures a lot of the dynamics that are going on right now in the environments. And I mean, for me, I come at this from an application developer standpoint. I actually, when I joined Cisco, I was not a hardware guy at all (laughs) Frankly, I'm not even now. I'm much more oriented towards software, and so when we've seen, though, sort of the power of the underlying infrastructure that gets married up to some of these overlay systems like Kubernetes and containers, more and more of the infrastructure on one hand is getting abstracted, which you might think, oh, uh oh. Like, that's a problem. But in reality, the infrastructure still needs to be there, right? You can't run your serverless function out of thin air. >> John: Yeah. >> At least not yet. >> John: It's truly not serverless. There's servers somewhere. >> Yeah, exactly. So, you know, those are the funny jokes that we like to have in the industry, right? But at the same time, you want to think like, okay, well I'm writing my application, I'm a developer. I don't want to know about infrastructure. My whole job is I don't care about that. But there is information and utility in the data that you can get from the infrastructure because at some point, your application will fail. You may have some bugs, and yeah, Kubernetes may kill your container and bring up another one. But you still need to de-bug that issue, and so yeah, you can get tracking, you can get analytics. But also, you can get that stuff from that infrastructure that's underlying it. And so, like one of the presentations I'm doing tomorrow, I wrote just kind of a proof of concept sample app where it's a Spring Boot app that has a built-in health check capability. It ties into APIC-EM and or DNA Center and uses that information that's available about the network. So maybe it's your, from your firewall to your application, you can run a path trace and just have that happen every five minutes or something like that, or check the health of an entire environment every, you know, so often. And then your application can resolve issues or have just data about it so that we can keep moving. >> Yeah, actually, you know, I love that comment you talked, you know, you're not a hardware person, and that's okay. >> Ashley: Right. >> And there's lots of people here at the Cisco show that aren't. That's a change from just a few years ago. How is that dynamic changing? You know, I remember for a few years I was arguing like every networking person needs to become a coder and there's, you know, push back and people are scared and what's going to happen to my job and can I learn that skill set? >> Ashley: Right. >> The bar for entry seems pretty low these days but how do we translate some of those languages? >> Yeah, I think that perception of say, an ops person becoming a programmer, it's not really the right mindset. >> Right. >> There's a couple mindsets, though, that are important. So one of the things we're trying to do is foster the DevOps culture somewhat. And to do that, an ops person has to understand and have empathy for the problems that exist on the application side and vice versa. So for us, we're just trying to education people in that vein. >> John: Yeah. >> But all of the infrastructure is now also automatable and you don't have to automate at low level. You can automate it with things like Ansible, which is a bit more accessible for people that haven't been programming for a long time. So, you know, I think those are the things that we see and that we're trying to encourage within our community and just broadly speaking, I would say, in the industry. >> You brought up empathy, interesting. Because this is a cultural shift, right? So this mindset, this cultural DNA, you have to have empathy. But it's kind of like the Venn diagram. Empathy is one circle. >> Ashley: Mhm. >> Feasibility is another and viability is the other, right? >> Ashley: Mhm. >> So it's always in context to what you can get done, right? So you guys at DevNet have a good view of the development environment. What are some of the challenges and what are the opportunities for folks in the Cisco ecosystem to get their hands dirty, get down and dirty with the tech-- >> Ashley: Oh, yeah. >> Where they can do feasible, viable projects that are possible. Well, seeing Python certainly is one approach. Great for data wrangling, but you know, you got Node.js out there, has been a great language. >> Ashley: Yep. >> App guys are doing Node.js because of JavaScript in server-side. >> Ashley: Yep. >> You got a lot of IO that sounds like a network service mindset. Is there things that you see going on around that what's possible and what's kind of moonshot like projects and where should people start? >> Well, I think, again, kind of going to this historical point of view, it used to be you had one programming book and you're sitting there, you know, late at night copying code from that. And maybe it came with a CD and you could download, you know, your sample code onto your hard drive. And then, you know, you'd be sitting there flipping back and forth and then you hit an issue. You're like, I don't know what to do. Maybe you're trying to teach yourself. I don't have any friends that are programmers. I mean, today, with, I built the vast amount of resources that are available online. You know, like, we have our DevNet Learning Labs. And so that's the set of tutorials that we've provided, but that's not the only thing out there. You've got Code School, Codeacademy. You've got the loops out there. I mean, shoot, MIT, Stanford, they're all putting their courseware in open-source. So the universe of educational material for people to understand this stuff and get started is really, really awesome now. And then also, it's easier than ever, I think,. to actually code because you're, again, like code is becoming more and more abstract at higher level languages. So Python, Node.js, those are still kind of low level, but there are packages on top of those, you know, middleware and Node.js, to build a web server. You get Express or sales or whatever, and then you're kind of off to the races. Like Spring Boot is crazy. It used to be Spring was a bit of a pain in the butt with, you know-- >> Yeah. >> Ashley: All the dependency, injection and everything. But with Spring Boot, now you just add, you know, a dependency, and you've got an entire web framework or an authorization framework or whatever. And that was like, I was pretty blown away when I started seeing-- >> So it's a lot easier. >> It's, yeah, it's just a lot easier. Things are more curated. You have certain stacks. You know, it used to be LAMP stack, now you got ELK stack for data things, you got, you know, and so on. So the universe is wide open for a lot of people to program today. >> So Ashley, love the training angles that you talked about there. But what I bring to mind, a little bit orthogonal to what we've been talking about here-- >> Ashley: Ooh, good programmer buzzword there. >> But one that John and I have been asking about, you mentioned open-source. >> Yes. >> So obviously, things like Spring, lot of things you mentioned are open-source. >> Yes. >> But what about Cisco's, you know, involvement in the community, giving back to open-source. What's the philosophical, you know, viewpoint-- >> Yeah. >> From Cisco's standpoint? >> Yeah, we're active in open-source. We're big contributors to OpenStack, for example. You know, we've got some of, we've created like a CNI module for Kubernetes called Contiv. And so that's in open-source. We, you know, in DevNet, we publish tons of things in open-source, just code samples and you know, example projects and so on. Cisco's actually a big contributor to the Linux kernel, so it's a long legacy of open-source at Cisco. So it's part of our culture. >> So there's no restrictions on everybody going on GitHub, throwing their stuff in, being part of the communities-- >> There's certainly restrictions. Yeah, we have processes that we're supposed to follow. I mean, we got to protect the intellectual property when we need to. I mean, it's the way it is for working at a company. But at the same time, you know, there is viable processes if it makes business sense to open-source things. >> I mean, the line John's used, you know, for the last year or so, is GitHub, that's people's resumes these days. >> Yeah, absolutely. >> So we want to make sure, what I'm saying is it sounds like the ecosystem at Cisco, friendly for the developers to come in, participate. You got a business to run, obviously. Legal keeps their eye on stuff, but you know, Cisco's out there. We saw it in the container ecosystem, OpenStack-- >> Ashley: Yes. >> Stu: Kubernetes, Linux, absolutely-- >> Yeah. >> Stu: Not just even in networking but beyond that. See a lot of Cisco out there, so-- >> Yeah, great. >> So my question for you, personal question. If you could talk to your 22 year old self right now-- >> Ashley: Oh, wow, yeah. >> You're high school, actually, you're college or college graduate, what would you say to yourself knowing what you know now? 'Cause this is a really interesting point. I mean, at my age, we used to build stuff straight up from the bottom of the stack to the top, and it was a lot of heavy lifting. Now you're really kind of getting into some engineering here and then some composite Lego block kind of thinking where these frameworks could just snap together. Sometimes (mumbles) But it's a lot cooler now. I mean, I wish I was 22. What would you say to your 22 year old self out there? What would you advise yourself? What would you say to yourself? >> Where's my smoking jacket? (John laughs) Yeah, so, I mean, I was a liberal arts undergrad and I did take computer programming classes. So I did a couple courses in C toward the end of my time in university, and that's because I've always been interested in technical, you know, in programming and stuff. But I think probably I would have maybe stayed another year to try to maybe get an actual CS degree. So that might be one thing, I think the other-- >> John: What would you jump on today if you saw all of this awesome code, open-source? I mean, like, it's like open bar in the coding party. I mean-- >> Yeah, it's overwhelming. >> It's so many things to jump on and-- >> You know, obviously, joking, I should say blockchain and machine learning and AI, right? But actually, I would say the machine learning and AI stuff is probably a good, interesting, you know, wave of technology, yeah. >> I just want to, you know, we're talking about your 22 year old self. How about your kids? >> Ashley: Yeah. >> You're working with your kids, checking out your GitHub on there. So, you know, maybe share, you know, younger people. You know, how do they get involved? In the keynote yesterday, it was, you know, jobs of the future. >> Right, well, yeah. For my kids, I have two daughters. And so, I try to encourage them to at least be familiar with coding. I've tried to teach them Linux some, but we've done programming classes, but it's kind of hard sometimes to get them interested in something like programming, to be honest. So some of it's trying to be creative problem solvers, trying to craft that sort of attitude, you know. So that then, when they do get the opportunity to do some programming, that they'll be interested about it. >> I mean, the young kids love gaming. Gaming's a good way to get people in. >> Yep. >> VR is now an interesting-- >> I mean, Minecraft and Sims, those are the two that my oldest daughter loves. I mean, the thing I remember that's the funniest was when you know, of course, this was when we all got computers back in the day and we did keyboards, right, in order to do stuff. So I got the first iPad when it came out and I brought it home and my daughter, who was, I think, six or eight at the time, she's like, "Cool, I understand this." Like automatically understood it. But then, she went to the TV and it had icons on it. So she walked up to the TV and tried to do that, and I was like, "Oh, that's funny." Like her mental model is this. >> Yeah. >> Where our mental model was that and so on earlier on. >> My oldest son says, "Dad, search engine is so your generation," (Ashley laughs) Not even email, like search, Google search. >> Yeah, the digital, it's like the digital native thing. On the other hand, we actually are fairly restrictive about like cell phone and mobile because it's a lot. That sort of thing. They really, really are going to face some interesting, I don't know, social, you know, the social things that you have in high school and middle school now multiplied and amplified through all that. We're sort of cautious, too, as parents, you know. >> Lot of societal issues to deal with. Alright, now getting back to DevNet here, I want to get your thoughts because we had a big setup here. One of the things that the folks people can't see on camera is we're in the DevNet zone. You see behind us, but there's everywhere else around. It's really the big story at Cisco Live and has been for awhile. Every year it gets bigger. It's like, it keeps growing in interest. What do you guys show here? What's the purpose? Give a little quick, take a minute to explain the DevNet approach this year-- >> Okay. >> John: And how it's different-- >> Yeah. >> John: And how you guys take this going forward. >> So the DevNet zone, philosophically, we tried to have the experiential. We don't want people to come in here and get death by PowerPoint of hey, check out this awesome new product that we created. You know, that kind of thing. >> Yeah. >> Instead, we want people to come in and have the opportunity to sit down, either by themselves or with a friend or, you know, with one of us to be able to work through sort of tutorials so that we have this area of the Learning Labs or learn about the DevNet sandbox. That's another area that we have where that is a sort of try it out, live, always-on, cloud service that we provide for anyone. We also have, of course, examples of example use cases. So we have some IOT and collaboration use cases that we're demonstrating in the new APIs that have come out of those products that you wouldn't think may be necessarily, oh, collaboration and IOT really are connected. But in fact, you know, ultimately you need to get a human involved when you have exceptions. And in a lot of cases like for edge compute scenarios, it's exception oriented. So when we, the example that we have here is we have a truck that's sitting on a handcrafted scale that's like a raspberry pie thing that one of our evangelists, Casey Bleeker, made. And it's putting, you know, analog data into our container that's running on an edge device. And when an exception occurs when the scale has this truck on it with too many stones in the back, then it triggers an alert. It creates a team room for people to come and escalate and discuss. It'll make a phone call automatically to the truck driver and pull people together to deal with that situation. But then, additionally, we have a new room capabilities with like, our telepresence systems. And that has face identification, not like from identifying the user standpoint, but it knows it can count how many people are in the room, for example. So if you combine that sort of IOT capability with this collaboration unit that's going to already be there, you're getting kind of a win-win of that infrastructure in the rooms. >> Ashley, talked about there's so many different things going on there, what's exciting you the most? Where are you seeing the most people, you know, gravitating around? >> Yeah, in the DevNet zone in general? >> Well, it can be here or in general, yeah. >> Well, I think one thing in the DevNet zone, we also have a white hat black hat challenge. So that's been very, very popular. What we're doing is demonstrating using, you know, off the shelf hacker tools, how vulnerable some IOT devices are to give people. It's kind of a you've heard about it, now experience it and do it yourself to see how easy it really is. And then see, of course, how our solutions can help you mitigate those problems. So that's, you know, IOT security is a big concern, I think, in general, and so I think that's an exciting spot for people-- >> So hands-on learning, very people-oriented, very open-- >> Yes, yep. >> The motto I love, I'm reading on the thing there, learn code, inspire, connect. So learn, toe in the water, connect-- >> Ashley: Yes. >> Share. >> Yeah. >> Mentor, collaborate. >> The other thing that we're sort of soft launching, I guess, is we have a new application developer site on DevNet, and so-- >> John: What's the URL? >> It is developer.cisco.com/site/app-dev. >> John: Okay, that's good. Memorize that, quiz later. >> Yeah. >> That's long, just search. >> Yeah, right, right. >> Hey, Alexa. >> Right, so, but with that, we're trying to make it easier for people to understand the use cases for what kinds of applications they can build using our technology. So indoor location, using kind of doing maps and heat maps and building that kind of scenario, for example. >> Awesome. >> Ashley: Through T-Mobile and video and such. >> As you are evangelizing your engine on the engineering side, what's the plans going forward? Post-event, obviously, you've got Cisco Live in Orlando this year, it's in 2018. >> Ashley: Yeah, we have-- >> But you guys got a lot of these going on, you got a lot of digital content. What's the outreach plan? Where should people expect to see you guys? Share the going forward plan. >> Yeah, I wish I knew where everyone was going to be. So thankfully, on the website-- >> They're on the internet! >> We have an events calendar, so I would definitely encourage you to look there if you're interested in connecting with one of us. We have the Cisco Live in Melbourne then Orlando. We also have DevNet Create in April and that's in Mountain View, I think, Bay Area. So would love to have people come out to that, and kind of the theme of that last year, which was the inaugural one, continues this year, which is where apps need infrastructure. So we want to kind of continue this conversation about DevOps, how, you know, applications and infrastructure-- >> John: Yeah. >> Can benefit each other. >> And just for the folks watching, theCUBE was at the inaugural DevNet Create. We'll be there again, we'll also be in Orlando. And again, this is important, we'll end on this point. I'd like you to take a minute to explain the difference between DevNet and DevNet Create because this is really interesting. I like the way you guys are doing this. It's really open, but it's pretty transparent. So share the difference between DevNet and DevNet Create. >> Yeah, so DevNet is our developer program, and so that's a website-- >> Before Cisco and-- >> It's Cisco, it's oriented towards those things. DevNet Create is more about forming a community to solve these problems about applications and infrastructure. So that intersection, whether you call it DevOps, whether you call it I don't know what, potatoes and you know, something. Something in there, you know, there is this fluid spot where applications are looking more like infrastructure, infrastructure is starting to look more like applications. So what does that mean and how do we explore that together to, you know-- >> We call it cloud-native. >> Ashley: Yeah. >> It's a set of developers who just, like you, don't really want to get involved in network but love it to be more magical. >> Right. >> Right? And Cisco folks love Cisco because they're in that world, right? So-- >> Yes. >> To me, it's really interesting you guys do that. Congratulations. >> Yeah, thanks. And it's not just for Cisco people, right? So Cisco Live and DevNet Zone is that. For Create, it's actually the inverse. We encourage people from the community to come and check it out as opposed to the-- >> John: Props to you guys, great stuff. Cisco, DevNet Zone is where theCUBE is. Of course DevNet Create is going to be outside of the Cisco ecosystem. Connecting the two is really the key. We're living in a world, global connected devices, connected people, that's the mission of Cisco. Love that vision, but of course, we're theCUBE, bringing you the live content here in Barcelona. All, of course, is available online, youtube.com/siliconangle. Of course, thecube.net is our new site. Check it out. I'm John Furrier with Stu Miniman. More live coverage coming from Barcelona with theCUBE after this short break. (upbeat electronic music)

>> Narrator: Live from Las Vegas, it's the CUBE. Covering AWS re:Invent 2017, presented by AWS, Intel, and our ecosystem of partners. (the CUBE theme music) >> Hey, welcome back everyone. Here live in Las Vegas, the CUBE's coverage of Amazon re:Invent. It's 45,000 people, lot of action. Again, three days of wall-to-wall coverage. This is day two, trying not to lose my voice. I'm here with Justin Warren, my cohost this week, along with Stu Miniman, Keith Townsend, and a variety of other great, great hosts for the CUBE. Doing our share to get that data to you. Our next guest is Kalyan Ramanathan, who's the vice president in product market at SumoLogic, but also the author with a group of people from SumoLogic on a great report that they have out called Modern Applications in the Cloud, and he came and he took some time to come from his meetings to come on the CUBE to talk about it. Because we've been riffing on what is a modern application? What is a modern cloud? You know that Justin and I were talking about this renaissance in software development. Obviously, the cloud wars are happening. The water's being pulled out, that tsunami's coming. It's changing the face of startups, IT, and developers at the heart of the action, a new cultural renaissance. Welcome to the CUBE. >> Thank you very much. >> So, a little editorializing there, an opining. But we believe that we are seeing a C change, a renaissance in software. Because the things that are now possible, the creativity, the power of developers, the end-to-end visibility into services is just like putting a PowerPoint slide together, or LEGO blocks. It's just like, it's so easy, not. But I mean, it could be easy, it's easier. >> Kalyan: Absolutely. >> So modern applications are top of our mind, so everyone wants to be modern. They wanna be hip, they wanna be cool. But there's some serious work getting done right now in the cloud. And there's a shift of greatness coming. What does your report show? Because we wanna dig into it. What the hell is a modern application? Is Oracle a modern application? Do I buy Watson at IBM? I see that on TV a lot. What is a modern application? >> Yeah let me, thank you John. So let me start with a quick introduction about SumoLogic, so that I can set a context about this modern application report. So SumoLogic is a cloud-native machine data analytics service, and what we do is to help our customers manage the operations and security of their mission-critical applications, right? The end goal to our customers is that now they can deliver an application with very good security posture and with exceptionally good customer experience. Now, we've been in AWS for about seven years. We have about 1,600 customers under management today. So what we've been able to do in this modern application report is to fundamentally mine data from our customers in a very anonymous way and give insight into what typically makes up a modern application in the cloud, right? And when we talk about a modern application, and I typically see three characteristics to these modern applications. First and foremost, many of these applications are indeed architected or perhaps I should say even re-architected in public cloud environments like AWS or Azure or Google Cloud Platform. Secondly, many of these applications are built using DevOps and Agile-style practices, so the rate and speed of change in this application is completely off the charts. The third thing that we are starting to see a lot more of is that many of these applications are built using Microservices-style technology, so it's very easy to compose these applications. You can put them together very easily, you can make changes to these applications a lot. So that's our typical definition of a modern application. >> Okay, well, we heard Andrew Jassy, I think, one or two days ago, was talking about if I started AWS again from scratch, today I would be using serverless. So I wouldn't be deploying virtual machines, I wouldn't actually be using a lot of the AWS services that we have today. So what are you seeing in the momentum for how developers are using the different types of stack. We're seeing a lot of growth in NoSQL, we're seeing a lot of growth in serverless functions. If I were starting a modern application today, what would my stack look like? >> Yeah, I mean, that's at the heart of the report that we put together, right? The report actually provides an end-to-end application stack, starting all the way from the infrastructure layer to the applications and even perhaps the management and the security technologies that you may need to manage these modern applications well. So let's start off with the infrastructure layer, right? So what SumoLogic has identified in, anonymously again, mining our customer data is that, you know, on the infrastructure side, Linux rules. As a operating system, goes without saying, Linux is the dominant operating system in AWS and that is to be understood. But here's the other interesting data point. Linux is also getting significant foothold in the Azure world. And that is not commonplace knowledge today, right? I mean, you would expect that Windows is ruling the Azure world, but we are actually starting to see dramatic year over year growth in terms of Linux within the Azure world. Now, let's move up the stack, right? Let's go from the host and the operating system now to the container world. What we are starting to see is dramatic growth in container adoption within AWS. Last year, when we put out the first version of this report, we saw that 18% of our customers are using Docker within AWS. This year, we are seeing that one in four customers are actually using Docker within their environment. >> Node.js, we saw a New Relic kind of report too. They laid out a little bit different instrumentation of it, with what languages. Python and Node.js, certainly Node.js, really awesome for the cloud and you're seeing that continue to be great. How does that gonna fit into Azure, for instance? What are they doing in their clients? So we were talking about Azure, right? So you look at their numbers, right? Azure versus AWS OS adoption. Okay, Linux is moving up because they made that announcement. But people have been looking at Azure and confused by the Azure stack. It's almost like a black box. Here, Amazon lays it out very cleanly. How is the Azure stack piece impacted? >> Yeah I mean, Microsoft, they've historically been a much more of a closed ecosystem. But I think in the Azure world, we are definitely starting to see Microsoft open the kimono, in some sense, and start to adopt, not just opensource technologies, but also technologies that are not very core to the Microsoft stack itself. A lot of our customers who are using us in Azure today, are, as I mentioned, they're using Linux in a fairly significant way. We are also starting to see Azure functions being used in a significant way. In terms of the entire application stack, again, Azure has, while they are behind AWS in terms of the number of services, the richness of the services, we are starting to see them catch up in a very significant way. >> All right, here's a Here's a pointed question for you, it's a tough question, okay? Maybe tough to answer, maybe you know the answer. A lot of people will try to fake it until they make it. And you've heard that term around. You really can't fake being a modern application, so what do you see as ones that aren't making it, in terms of architecture and stacks? Maybe it's Legacy trying to bolt on a little bit of glam front end, Javascript, or Node. Where's the failure, or having one relational database, maybe Oracle and trying to blend that in? Is there a formula that you see that's not working? >> You know, I think the act of just putting on a shim around a Legacy technology and calling that modern, I think what we are starting to see more and more of, is that that can take you so far, but only so far, right? The underlying infrastructure technologies of today, especially containers and you guys heard Andy Jassy talk about Kubernetes today at his keynote. There are such technology advances that are so core to the architecture of the modern app that if you choose not to implement them and if you just put, in some sense, a lipstick on a pig and a tiny little shim on top of a Legacy application, >> Sprinkle a little bit of glitter on things, yeah. >> You're, can you get away with it for a year or so? Absolutely, but then you're talking about, you know, dealing with extreme scalability, high elasticity, security of the kind that is needed for most enterprises. That's where the Legacy technology and just a sprinkling of dust, as you described it, is going to fall apart. >> I love the top two data, two of the three top datas are NoSQL. Interesting you got MySQL, Redis, Mongo and PostgreSQL, and then Cassandra and then Redshift. Redis, really kicking ass at number two. >> Kalyan: Absolutely. That's surprising. I always loved Redis but that's moving up. That's ahead of Mongo. >> Yeah, absolutely. I mean, Redis has a huge following. It's a in-memory database, as you know. It also has a lot of shades of NoSQL. >> John: It's flexible. >> It's very flexible, absolutely. So I mean, the interesting data point in the database analysis that we did was that in the cloud world, NoSQL and SQL are pretty much head-to-head, right? So, I mean the way we think about it is, when you are re-architecting your applications to the cloud, it really gives you the opportunity to step back and say, what do I do with my data store? Does it have to be the Oracle of the past? Can I re-architect it for something that's more optimized for what I'm trying to do now? And that's where, I think NoSQL has really caught on. >> We, you know Justin, we were talking yesterday, and then Andy's keynote. I had one-on-one with him a week ago. It's good, some of my content made it into his keynote, because one of the things I've been banging on we talked about yesterday was, these modern databases, modern apps, could have multiple databases. And you, look at Redis, there's different use cases. DynamoDB is slow on lookups, I might wanna have a queue there. I might wanna tie it with Redis and a little bit of architectural shape. It's a whole new normal, it's not a one trick pony. >> Yeah, and Redis is really popular in the Kubernetes community, I know. So as we see Kubernetes growing, then I expect that the Redis growth will also follow that. >> The question is, this is what I've put, and he put inside his keynote was, the new modern app can have multiple databases. This is gonna have a huge impact. How does that impact this report? What do you see, because now it kinda changes the game? It's not one, I can't just throw MySQL at it, or Mongo. Used to be the old days, LAMP stack and say, okay, Mongo's awesome, I'm gonna build my app, but now I gotta integrate it with another app. >> Yeah, no, absolutely. I mean, we're seeing heterogeneity across the board, right? And that is part of the goal of a report like this, too. Right, I mean, we put this report out mostly focused on cloud architects, DevOps engineers, SRE engineers who are rethinking what it takes to run an application in the cloud, may it be AWS, Azure, et cetera. And we wanted to provide them a roadmap of what are their peers doing in this world. >> Well, we really appreciate you and SumoLogic doing a report. New Relic has one. We love these kind of reports and when they're this good, we like to talk about them. I know you're being really nice and you don't wanna lose customers by pissing off other cloud guys, because you're in Switzerland, you play with all of them. But there's really some interesting data here that points to who's leading and who's not, and then the stacks do matter. The developers are influencing IT decisions now. So knowing the stack, knowing your stack, what works for developers, super important. We're gonna keep track of it. We'll certainly invite you into our powwow out at the studios to do some check-ins on the report. Maybe do a deeper dive, appreciate it. >> Yeah, and all I'll say is this report is available on our website. It's, you know, you don't have to register, you get it. >> John: Free. Yeah, it's free. >> They don't even ask for an email address, which is great. (laughter) So thanks so much for SumoLogic. Thanks for coming on the CUBE and breaking down the report. More live coverage here from Las Vegas, from Amazon re:Invent, I'm John Furrier with Justin Warren. We'll be right back with more after this short break. (the CUBE theme music)

(motivating electronic music) >> Hello everyone, welcome to theCUBE. I'm John Furrier, the co-host and co-founder of Silicon Angle Media. We're here for a CUBE Conversation in our studios in Palo Alto, California. Here with two great guests inside the industry, to help illuminate the cloud computing conversation, really around what's coming up with Amazon re:Invent. But more importantly, the major advances happening in the digital transformation around IT and around developers and around cloud, and how that's impacting business. Our guests are Chris Comings, who's with the Chasm Group, consult and they help people, and former industry executive at NetApp, and (mumbles) the storage company. Peter Smails, the CMO of Datos.io data, and then he's the CMO there. Now, new progressive solutions. So guys, great solution. And Peter, I know you got news. We're gonna do another segment on your big news coming out, so we're gonna hold that off. >> Cool. >> The game has changed, right? >> Mm-hmm (affirmative). >> And we talked, with Chris and I had a one on one about this. But the industry conversation, there's people that are in the know, and people who are trying to figure out what's happening and how it impacts their business. CIO, CEOs, CDOs, chief data officers, chief security officers. There's a lot of things on the plate of businesses. >> Right. >> Big time. >> Right. >> So let's unpack this, and let's illuminate what it means. So cloud computing, Peter, what's your take on this, because Datos just takes a unique approach? I love your solution. A lot of people are liking this solution, but it's nuanced, because it's cloud-- >> Yeah. >> That's driving you. >> Yeah. >> What's the big driver? >> So the big driver, you said at the top of the discussion, the big driver is digital transformation. Digital transformation. Organizations are trying to be more data-driven. Okay, this is completely throwing, throwing traditional IT amok, because we're not living in the traditional world anymore of all my data sits within a single data center, I run my traditional monolithic applications. That's changed. The world is no longer running in a traditional four wall data center, and the world's moved away from the traditional view of scale-up architectures to elastic compute, shared nothing, elastic storage environment. So what's happening is, you've got the challenge of trying to essentially support traditional transformation initiatives, and it's just throwing all the underlying infrastructure foundations that an entire generation of IT professionals has known (laughs) into disarray. So everything's a little bit caddywhompus right now. >> Mm-hmm (affirmative), Chris? >> Well, and like you said, those people all have gone from being implementers to, they're moving to being developers. >> Right. >> And it completely changes their, it has to be a big change in their mindset. And it changes the management folks, the CIOs, the CDOs, the people that you interact with on a daily basis, right? >> Absolutely. >> Because these people are all trying to kind of come up to the next generation and get there. >> So you talked about, we got re:Invent coming up in a couple of weeks and, I think reinvent's a perfect term for this entire conversation, because everybody is reinventing themselves. The customer's reinventing themselves, the IT organizations are reinventing themselves, the individual roles within organizations are changing, and the whole evolution of dev ops versus traditional roles, so it is really-- >> And the vendors are all trying to reinvent themselves, too. >> Yeah, absolutely, absolutely. >> Well there's a lot of noise, so the customer's being bombarded with pitches. And if I here one more digital transformation pitch, without substance, I still don't understand. So in the spirit of trying to understand, first of all, I believe in digital transformation, but you can't just say the word, you gotta to prove it. But there's hard to prove a new approach or they've never seen it before. It's kind of like Steve Jobs would say, "If you want a Blackberry, that's a phone, "but the iPhone's not what you've seen before." But everyone loved it, changed the industry. That dynamic's happening in the cloud where for instance, your solution, some might not have seen before, but it's highly relevant to the user behavior expectations of the new environment. Okay, so this is the issue. What is the new environment specifically around digital transformation? Because I have an investment in storage. If I'm a customer, I bought a zillion drives from NetApp and EMC. I got data domain backup and, I got a perimeter, I have all this stuff, and now I've got this cloud thing bursting, and I got some analytics running there, and then I got the hot shot young developers banging out apps, and they want to put it in the cloud and... and security, I mean, what's going on? >> You wanna take that one first? And then I'll jump in. >> Can't I just buy more storage? >> Yeah. (Men laugh) Hey, just, no John, you don't just buy more storage, you upgrade from spinning to flash. I mean, that's really, >> There you go. >> That's really, really cutting edge right there. No I think what a lot of you see what they're doing is basically saying listen, for all this secondary, tertiary, quaternary, I mean, I didn't even know what that word was. But your second, your third, your fourth cuts of that data, move that all to the cloud, get that out of my environment. I'm not gonna be submersed in dealing with all of that anymore. Then maybe I can clear out some of my headaches, so I can actually focus on that primary cut, and what do I do about that primary cut? And that's where these completely new approaches come into play, and I, Peter I don't know if you call that hybrid, or multi-aire or what? But it is basically just trying to get some of that noise out of their system, so they can focus on the thing that's most valuable. >> So the way I would make that tangible John, is sort of, to us it all rolls down to the notion of the modern IT stack, okay? So essentially, the way you respond to digital transformation which, is all about being more agile, and some of the buzzwords you hear, but they're trying to be more, customers are trying to be, vendors are trying to be, or excuse me, customers or organizations are trying to be more customer-centric. They're trying to be more business driven, more data driven, okay great. If that's their initiative-- >> That's a mission. That's a mission. >> That's a mission. >> Yep. >> What that means for IT specifically is a fundamental rearchitecture of the underlying stack, okay, along a couple vectors, which is, organizations are building these new applications. They're fundamentally rearchitecting applications. What used to be a monolithic-oriented, traditional, relational, on-prem database is now running in a microservices, highly distributed configuration. That's vector number one, implication. Implication number two is we're absolutely in the mainstream of hybrid cloud, okay? You may be running all your apps on-prem, but you're still connected in some way to the cloud, for archiving, for BI, for TASDAV, whatever the case may be. And number three is the world just moved completely to an elastic, compute, shared nothing world. So we call that the modern IT stack. So the modern IT stack, modern infrastructure today-- >> Share nothing, you said? >> Shared nothing, the cloud is-- >> Oh, shared nothing. >> Yeah, shared nothing, shared nothing storage, shared nothing compute, that's that's, those are the foundations of a cloud based architecture. >> Is that called serverless? >> You could call it serverless as well. >> Okay. >> But, if you look at the modern IT stack, so to your point, the modern IT stack, modern infrastructure today is EC2. >> Mm-hmm (affirmative). >> Modern storage is S3. It could be object prem, object storage sitting on-prem. You know, modern applications are IOT. Modern, or our customer 360, IOT. Modern databases are dynamo DB. It's MongoDB, it's the number two-- >> Right. >> database in the cloud. So to answer your question very specifically, to make it tangible, that's to us the fundamental indication is, that new modern IT stack, throws storage into disarray, it throws data management into disarray-- >> It's an operational disruption. >> It's an operational disruption. >> All right, so let's backup for a second, because I think you nailed the thread I was trying to connect on. So let's take MongoDB, your reference to that being, where'd that come from? We all know why, the LAMP stack, it was one of the drivers. But developers drove that. >> That's right. >> So it wasn't the IT department recommending Mango. >> Right (laughs). >> so the developers were driving that because of ease of use. Now there's some scalability with Mango, we all know about, but what that means is, no one gives a crap if it can scale, because you already hit your product market fit. Then you could rearchitect, so you're seeing this use case of developers driving some of the behavior. >> Yes. >> Yes. >> Mm-hmm (affirmative). >> Hence containers, docker containers, and the role of Kubernetes. >> Kubernetes, yep. >> So if that's the case, how does an enterprise customer deal with that vector? Because now the developers are dictating the stacks. >> Mm-hmm (affirmative). >> Well, I-- >> Is it a free-for-all right now? I mean, this is... >> I think both of those guys are, think of it as they used to be warring factions, dev and ops, and the fact that we say the word dev ops right now is kind of a, it's kind of an oxymoron, right? Because they don't actually know each other and actually don't naturally talk to one another, and they go, "That's the other guy who's holding me back." >> Yeah, it's the old-- >> They look at, yeah, yeah. >> Goes over the fence. >> And so now, you've got folks that are really trying to, trying to bring it together a little bit more on that front and I think that, we're starting to see some technologies where people can say, "Not only can I use that "to accelerate my developments," so meets the dev criteria, but also the ops people say, "You know what, that stuff's not so bad. "I could actually work with that." >> Right, and then there's IT going, "Uh-oh," because they're basically sitting there on the catcher's side, so to your point it's, the dev ops, it is very much of an application-led environment. The tip of the spear for the new IT stack is absolutely application-led. And IT is challenged with essentially aligning to that, collaborating with that, and keeping up with that pace of change. >> And John, on this point, I think this is where, back to re:Invent, and really the role of AWS. This all started because of that. When a developer can just say, "I don't even know who those IT people are over there, "But I can spin up my S3 instance, "and I can start working against it." They start moving down the path, they show it to somebody, someone says, "Wow, that's great stuff, I want that." >> John: Yeah, right. >> Guess what? We need to make sure that that's enterprise class and scalable and then that's where that whole thing starts, and then it becomes that pull-ya-apart, "Oh God, what did these developer people do? "I'm gonna inherit this? "What the heck am I gonna do with it?" Now it's, we've gotta move that to be more symbiotic up front. >> I remember talking to both Pat Gelsinger and Andy Jassy years ago, I think maybe five years ago, and I asked the question, "What enables developers?" What is enabling point? Does infrastructure dictate developer behavior? Or do developers dictate infrastructure behavior? This was years ago, when the dev ops was an early-on movement. Clearly the vote is there. Developers are driving infrastructure. Hence the dev ops infrastructure, >> Absolutely. >> Yeah. >> as code model, that's proven. Jassy was interesting because he looked at it that way and said, "Yeah, we saw the same thing," and they've never wavered, Amazon's stayed on the course, and they've just been running like a machine, like a, just pounding it out. I asked Pat Gelsinger, he once positioned the AWS as the developer cloud. Kinda in, I wouldn't say depositioning them, but he was basically pointing out, they have a developer cloud. Now Amazon's the enterprise cloud. >> Mm-hmm (affirmative). >> Because they've developers are now a big driver of that, and the scale with data is actually turning out to be a better security environment. >> Right. >> For cyber. >> Right, it might just-- >> So it's cloud's winning. >> Cloud is winning and just sort of just take that one step further. It's always ultimately, the winner's going to, it's Darwinism, it's like the winner's gonna be the one with the richest ecosystem. And AWS is becoming that enterprise eco. And you could argue, I mean, GCP's fighting to be in there, Oracle's not going to go quietly into that dark night. You've got multiple public cloud vendors. >> That's right. >> Yeah. >> But the reality is that he who has the biggest, he or she who has the biggest ecosystem is gonna win, and that's right now is AWS driving that bus. >> All right, so I need to see those glasses for a second, and then want to go into another line of question here. (men laugh) >> You may use those. >> Oh who's, oh you put them on, all right good, as long as he's wearing them. >> He that wear-- >> You know, on that front too, on that front too, I would think we started back where VM was the big new thing, and here we go with VM's, and then all of a sudden we're coming up and we're saying, "Yeah, now there's containers." And so now we're gonna see this move to, we want to micro-package these services, and be able to aggregate them. Well you know the average IT shop that I would be talking to out there is just still trying to figure out, how do they put together their on-prem and their AWS instance? So this notion of hybrid is where most of these large enterprises are. We see a lot of terminology out there and a lot of vendors talking about multi-cloud. But multi-cloud is really just taking an option on the future and saying, "I'm not locked into you, AWS, "even though I am locked into you 100% right now. "I don't want to be forever in the future." >> It's a value statement that they're gesturing. >> That's right. >> Good segue. >> Chris: But it's not a practical implementation piece. >> I got my nerd glasses on so-- >> Peter: Strap in for something, here we go. I got my nerd glasses, so next question, we'll go a little nerdy, because this is important one. I put out at my crowd chat for Amazon, so to crowdchat.net/awsreinvent it's open, I have a lot of questions on there. Feel free to weigh in, it's an influencer-only chat, so no consumers, so I asked the question, and this is to the value statement, because multi-cloud is basically telegraphing lock-in. We don't want lock-in. >> Right. >> But we want love choice. If you have good choice and good value, we'll go there so it's a value equation. So the question I said is, where do you, this is a question I put on crowd-chat, I'll ask you guys. Where do you see the value that cloud creates for customers in the next 24 months? #cloud So the first response was from Subbu Allamaraju, who's the CIO at Expedia. He writes, "Agility from the service "ecosystem and rapid second-order architecture "architectural changes thereby clearing technical debt." And the second one from Grant Chase, "Born on the cloud apps already here. "Next wave migrating of existing apps." And then Maddoux Tsukahara said, "Legacy SASS applications will be disrupted "by cloud microservices, serverless, "and AI and machine learning." So we start to see the pattern. Your thoughts? Value creation, in the cloud, is gonna be what? >> So I think they're hitting on the right trends. I would go back to the first one which is "How do I get this on-prem stuff "that's driving me crazy, consuming all of my resources "in terms of maintenance and upgrades? "And then optimizing my environment for that." Which ones of those are core? And which ones of those are really kind of ancillary? I've gotta have them, but I really don't want them. If I didn't have to use them, I'd get rid of them. Take all, just do that homework. Separate the two cleanly. Move ancillary to the cloud, and move on. >> Peter: Yeah, yeah. >> So service ecosystem he nailed, I love, by the way, I agree with you, that was my favorite answer. And rapid second-order architecture changes. This speaks to what datos.io is doing. Because you guys, what you're in, the tornado that you're in, kind of just a play on the Chasm group here. You guys have a solution that has got visibility into some of the real dynamics of the environmental environment. >> Check. >> People, tech, stack, et cetera. >> Yeah, yeah. >> So what are some of the things that you're seeing that point to these second or level architectural changes? >> Well you mentioned, a couple different things, which is, you mentioned the notion of technical debt, which is indirectly what you were just talking about, the ability to get rid of my technical debt. It's an easy way, it eliminates my barrier to answering to creating net new applications. So without having to sort of, I avoid the innovator's dilemma if you will, because I can build these net new applications, which are the things I have to to drive my digital transformation, et cetera. I can do that in a very cost-effective and agile way. Meanwhile, sort of ignoring the old world. Then what I'll do is I'll go back, and I'll worry about the old stuff, and I'll start migrating some of that old stuff to the cloud. So in the context of, yeah, so what we see from a Datos IO perspective, in the context of data management, is that one, applications drive the stack, like you said earlier, it's absolutely, the application's at the tip of the spear, driving the stack. Organizations are building net new applications that are cloud native, okay? And they're built on the new modern IT stack, and at the same time, they're also taking their legacy application, so I like that second answer as well which is, modern cloud applications are here. The interesting thing is, you say modern cloud apps, modern cloud apps don't have to run in the cloud. >> That's right. >> We've got customers that are running their next gen app-- >> It's an operating model. >> It's an operating model. We've got customers running 100% on-prem. Their econ number stuff runs on-prem, then you have people that run in the cloud. So it's a mindset, it's an operating model. So you've got folks absolutely deploying these cloud-native apps. >> Well, it's an architectural model too, it's how they are deploying and servicing apps. >> And ultimately, it comes down to the architectural model. That's what shifted, and that world is very infrastructure. The other thing I would add to the cloud thing is if you do it right, the cloud actually can give you architectural independence and cloud independence, but you can't be focused on the infrastructure level. You've gotta focus at the application level, because then you can be agnostic, until they're online. >> So Peter you, you guys are disrupting a very large space, backup and recovery in the cloud which you guys are doing. >> Check. >> And the application database layer is a very progressive solution. So I love your approach, but you're talking about disrupting the data domains of the world. We're talking about big whales. >> Yeah. >> Big incumbents that are built around four walls in the data center. >> Check. >> Mm-hmm (affirmative), yep. >> What are you seeing? What's the makeup? What's the personnel of the customers look like? If dev ops is happening, which we agree it is, and the the evidence is there clearly, they're not 50 year old backup and recovery guys. They're young guns, they're probably not thinking about waking up every day with their coffee, say, "Hmm, what am I gonna do with backup today?" >> Yeah. >> Mm-hmm (affirmative). >> They're waking up saying, "Hey, I'm gonna drive some more machine learning "and AI in my apps." >> Yep. >> "And I'm gonna provide workflow movement to--" >> And you said breakfast was some, you said that. >> Adopt this microservice. >> I had the craziest dream last night. It was microservices, what? >> Yeah. >> Yeah, so I can answer that two ways. There's the technology side of it. Fun little tidbit, average age of the traditional backup and recovery software architecture, about 20 years. >> Hmm. >> Architected well before the mainstream advent of the cloud or certainly modern applications. >> Hold on, the person's 20 years old? Or it's 20 years of architecture? >> No, the architecture of the software. >> Okay. >> The solutions, or come up, the point is they've been around for awhile. >> It's old. It's old. >> It's old, fair enough. >> Yeah, and 20 years-- >> So on the technology side, that's a dilemma. On the persona side, you're absolutely right as well. These are, it's the application folks that are driving the conversation, that our applications dictate the IT stack. They're building these new architectures, which have all these implications on the infrastructure. >> All right, so I'm gonna play devil's advocate, just because I want to connect the dots. And again, illuminate what I think the problem is that you have. One is, okay I'm a CIO. Hey, he's my storage guy. Who the hell are you, young gun? Complaining about your backup and recovery. He recommends all flash arrays in the data center provisioned in a VSAN environment, whatever that's going on. Who are you? You're just nothing to me. You don't make that decision. >> I'm the guy that can give you all the visibility to your data to make you smarter and more agile as a company. I can save you money. I can make this company more market-- >> So what do I need to do differently? If I'm the CIO, I don't want to make these, or these architectural calls based upon old dogma or old reporting lines. This is an example. I go to him, he's my storage guy. Who are you? I already built you the dev ops environment. He runs storage and so, you're impacted as a developer. So how do you guys talk to that guy? What does the CXO have to do differently to adapt to the new environment? >> I'll take that and then you can-- >> Please. >> You know, jump in. So I think what you see is, you see the proliferation of new personas. Like you see chief transformation officers, you see chief digital officers. You see system architects and DBAs getting a more prominent role in the conversation. So the successful CIOs and technology officers are the ones that are essentially gonna get the cowboys and the Indians to collaborate more closely, because they have to, because the folks that were over in the corner that used to get laughed at, building these, oh mangos and these new applications and such, they're the ones holding the keys to the future. So the successful technologists are gonna be the ones that marry those personas from the application side of the house with the traditional storage, infrastructure folks as well. You successfully do that, then you can be more, then you can move more quickly forward. >> Yeah, that's right. >> What do you think? >> Well I think some of it's gonna come back down to economics, too. And I agree with that move which is, I talked to over a hundred CIOs and their staff in the last year. I had one conversation where the person said, "You know what? "The chief complaint about me as CIO "is I'm not spending enough money." And I thought to myself, "Sounds like a company that I should put some bucks into, "because they must be doing really, really well." Everybody else is looking at it saying, "You know what? "I'm under pressure to adopt the cloud, "because there's a belief out there "that the cloud is gonna be so much less expensive "than what they've done in the past." And then I think they find that it's not, that it's not just the one size fits all answer to that. >> Right. >> And so as a consequence, you're gonna have people say, Listen, this money printing operation, or this funnel out the door to, whether it's EMC or NetApp 4, or whatever it may be, whatever storage vendor for backup architecture, they've got to stop that funnel. Because they've got to take what they were spending there and move it to the things that are going to make money for them, not just gonna hold on to it, and de-risk their enterprise. >> I'm here with two industry leaders, Chris Comings and Peter Smails, talking about the impact of infrastructure technologies, and app development in the cloud for businesses. It's a great conversation, and our final point, I wanna just get to, I know we're running on some time here but we wanna go a little further. I think this is awesome. That's for taking the time to share it out. >> It's great. >> One of my other questions I put on my crowd chat was, a true or false and comment question. Here's the statement: Serverless computing will become mainstream, will come to mainstream private cloud, true or false, comment. Subbu said, "False, adoption and success "of serverless patterns depend almost entirely "on the strength of the ecosystem "that the data center lacks." Interesting comment. I was kinda leaning, I go, "I was leaning towards true." But I don't have enough insight on this, because I'm waffling between true or false. I love serverless, I love the idea of, notion of resources that are just programmable. But what is the state of serverless? I mean, is he right? Is that that there's not enough ecosystem in the data center areas or... >> You wanna go first? >> Well, I'd just say that I would, I would just call out two things on that front. One is, I think you need a lot more germination of microservices that are out there in order to be able to put that all together. That's one aspect. We're seeing that growth come rapidly. The other thing is, now your security is beholden to the lowest common denominator. The security of that individual microservice. So I think you're gonna have some fits and starts here as we move down that path because, boy oh boy, the last thing I wanna do is get all modern but at the same time, put myself at a greater amount of risk. >> I thought the comment at the end was, I think it's true. I thought it was interesting what he said at the end. He said, "The ecosystem that the data center lacks." I would contend that potentially, the ecosystem that the cloud has would support that. >> Yeah. >> Because the cloud, by definition is, it's a shared-nothing world. >> Right. >> You know? >> So, he also comments, someone said, Lambda, "My Expedia is that Lambda's growth "is almost entirely due to the power "of the ecosystem of services, "which is one of the key points," and he points to his blog post. Stu Miniman, our Wikibon analyst weighed in, because Stu's on this big time. "Service will definitely be used for edge applications. "Currently don't see use case for general data center usage." >> Mm-hmm (affirmative). >> So edge of the network. Again, good point? This edge of the network thing helps you, because most people are using cloud for edge. >> Peter: Right. >> So this IOT, which is, an iterative things, is an edge of the network. >> Yeah, yeah. >> Whether it's devices, sensors, industrial equipment, or people's devices on their bodies. >> Yeah. >> It's a huge data source. >> Absolutely. >> Cloud's rolling that up. Or a cloud-like infrastructure. >> Well but it's not necessarily rolling it up. It's just connecting all the dots as to where you can put storage and you can put compute where the data is. Or you can move the data to where the storage and the compute is. So it's not, I mean, yes there's core and edge, that's absolutely true, but the notion of rollup isn't necessarily true. It's not necessarily the cloud enables me to do all this colossal aggregation. It's I basically distribute my compute, I distribute my storage. >> Well, when I say rollup, I'm assuming there's some sort of architectural thing. >> Okay, fair. >> But this fits into your wheelhouse, I think. But I just connecting the dots. That's why it's a question for you is, it would make sense for a solution like DATOS to be there because, That's a application so you-- >> Absolutely. >> You back up IOT? >> Oh absolutely. We backup IOT, but we basically backup any modern cloud application. And by definition, what does that mean? >> So IOT's and app for you. >> IOT, absolutely IOT's-- >> Not necessarily a-- >> So the technically where we plug in is, we plugin at the database level. And the databases basically, are the underlying infrastructure that support the applications. So in the case of IOT, those are typically very highly distributed across GIOS, absolutely we protect them. >> So we were just talking earlier about the words flexibility, manageability, agility. That's kind of vanilla words that everyone uses these days. But in essence, you're actually really doing it. Right, so. >> Thanks for that setup. Yes, we actually do all those buzz words. >> So Chris recommends, I recommend that you call it, hyper flexibility. >> Yeah. >> Or microflexibility. >> Or ultra. >> Or ultra flexibility. >> Or go mega. Just go mega right now. Or uber and steal a little of that, although that's kind of out of favor right now. >> Not, uber is-- >> Uber we wanna let that one kind of fly by. >> But remember we also talked before, we thought we were spot on with our product being branded RecoverX. We thought we were really in the spot with the whole, you know. >> Your name is awesome. RecoverX is a great brand. >> So we're gonna stick with that for now before we-- >> Good branding, RecoverX, Data IOS. Chris, thanks for coming on. Final comment, any words on the storage industry as it evolved? You mentioned earlier, just call it flash. Certainly, all flash arrays are doing well. Pure Storage went public. Flash is a standard. >> Yeah. >> It has benefits. Where does the flash storage go with all this cloud value coming over the top? >> Well I think, you know, there's gonna be a couple. I have one comment on that which is, we see what flash is doing at the array level, and now we're gonna see what NVME does at the cash layer, for allowing this access to information. You think about, I want to run a singular query, but some of that data is here, there, everywhere, but I've gotta have a level of performance that allows me to actually run it, and get an answer from it. And so that's where that comes into play. I think we're gonna see a whole host of folks flooding into that space, to try and improve performance, but not only improve performance, but enable that whole distribution model. >> Yeah, and I would just pick up on more persona-centric thing which is, the message to the traditional IT shops is it is all about collaboration. The folks over in the corner, the application folks, it is absolutely all about getting more closely aligned, because cloud is here. >> Yeah. >> Multicloud, hybrid cloud, call it whatever you want, is here. The traditional IT stack is absolutely being disrupted, and it's all about embracing this application-centric, data-driven view of the world. That's the future, traditional IT's got to align with that, and collaborate and drive that whole thing forward. >> That's a great, I agree 100% what you guys just said, great comment. I would just say Wikibon calls it unigrid, which is, I'll rename it hypergrid, meaning it's just one system, to your point. Private, public, it's all cloud-like. >> Absolutely. >> Yeah, it doesn't matter where it goes. Okay guys, thanks for the thought leadership. Peter Smails and Chris Cummings here, breaking down the industry landscape on storage infrastructure, application developers, in context the cloud. This is theCUBE conversation. I'm John Furrier, thanks for watching. (motivating electronic music)

>> Narrator: From Hell's Kitchen in New York City, it's theCUBE. On the ground at Serverlessconf. Brought to you by SiliconANGLE Media. >> Hi I'm Stu Miniman, here with theCUBE at Serverlessconf in New York City, really excited to have on the program one of the keynote speakers and a first time guest on theCUBE, it's someone I've know through the interwebs and have read his stuff for many years, Simon Wardley who's a researcher with a leading edge firm, Simon, great to see you. Thanks so much for joining us. >> Thank you ever so much for inviting me. It's a delight to be here. >> Alright, so my understanding is thanks to this event, you've reached a lifelong career goal. You're now a Sith Lord? (laughing) >> Well, somebody basically took a quote of mine and put it on a Star Wars poster with The Empire at the bottom, so yes, it is absolutely there you are, I am a Sith Lord, so delightful. >> The quote was that Serverless will just fundamentally change the architecture of how we build things. Something along those lines, I believe. >> Absolutely, yes. >> Alright, so let's start there. There are so many, come on, we all got really excited when containers came out. We're going to talk to John Willis >> You did. (laughing) >> We're going to talk about unikernels. The industry as a whole, there's frothiness and buzz >> Okay. >> So Serverless, you know, how's it different? How's it the same? Why's it so important from your standpoint? >> So, really good questions. So, to explain that question, we have to start off with a subject that is dear to my heart which is mapping. So when we look at the value chain of any organization, the components in that value chain are evolving and they evolve from the genesis, the novel and new to custom built examples and eventually products and rental services and then commodity and utility services. And that process is driven by supply and demand competition. It happens not only to activities, but to practice and data, but we give them different terms. They have all of the same characteristics as when they evolve. Now, when you look at that evolving environment, what you discover is there are two basic forms of disruption. There is the highly unpredictable form, which either occurs due to the appearance of something novel and new, which we don't know what it's going to impact or to product substitution. So that's the Nokia versus Apple, sort of battle, you don't know which way it's going to go until after the battle. And there is a second form of disruption, which is much more anticipatable or predictable and that is the product to utility change. So we know that when things evolve from product to utility we're going to see a rapid period of change and then there's a punctuated equilibrium. Explotion of higher order systems. We're going to see co-evolution of practice, disruption of past companies stuck behind inertia barriers. Yes it's going to be a bad efficiency, no we're not going to save any money 'cause we're just going to do more stuff with it and we're going to have all these new things as well. And we can anticipate that in advance. So when you start looking at value chains of organization, it's always the shift from product to commodity and utility which makes the big transformation in industry. And so one of them was compute. Shifting from products, as in servers, to utility as in cloud. Unfortunately dreadful term, cloud, an awful word, you know it's not a wispy thing up in the sky, it is something very specific, the shift from compute to utility. >> Would you put virtualization along that continuum? >> Okay, so virtualization was one of the underlying components, which actually helped with that happen. >> Yes. >> And so you've also got the explosion of practices around that co-evolution of practice, things like DevOps. Well, the same transition is now happening in the platform space. So, we're moving away from a product stack, things like, LAMP and .NET, to much more utility-based code execution environments. And that's what we're getting with Lambda. And we're going to see an explosion of new things built on top, inertia barriers, companies stuck behind, they'll die off, It'll be a rapid change punctuated equilibrium. You'll get all sorts of new things built. So we're going through that big transformation. Now, these transformations have been going on for about 300 years, some of them impact micro scale economics, some macro, the biggest we call ages. And that all depends upon how widespread that component is in other value chains, so when we're talking about software, we're talking about a component which is in almost all other value chains, it's shifting from product to utility, massive change, highly predictable. This is what Serverless is about. So, will it change everything? Absolutely it will. >> Alright, so Simon, I'm wondering, if you've mapped out for Serverless, where's the land of economic expection, the land of happiness and the land of despair? (laughing) >> Well, okay, happiness, despair and expectation? >> Yes. >> Okay interesting one. So the land of despair will be getting stuck behind the inertia barriers, dismissing it, saying it's not going to impact, it's not going to impact, no, no, because there's a punctuated equilibrium, it'll surprise you because it's an exponential growth, so you'll think you've got loads and loads of time and 10 years from now, you're like, be panicking, oh my gosh, it's impacting, I can't get the skills for people to help me do the transformation. My entire industry and business model is starting to disappear, so that is the land of despair that's coming to people, that's easy to defend against because most people can't see the environment. They're going to just walk straight into that one. The land of happiness. Well, obviously other than being the utility providers who'll be extremely happy about the growth of their industry, another area of happiness will be some of the novel and new things built on top. So, we're bound to see the, sort, of, one person, two person company who builds a fuction which is sold through something like the marketplace and everybody uses and they sell it for a billion. So, we'll get the two person billion dollar company and I'm sure that will make them delightfully happy. So, that's despair, happiness, also inflated expectations. So one of the big lies will be, Serverless is going to save me money in terms of reducing my IT budget. I'm afraid not. This is Jevons Paradox, this is being going on since 1865. All that's going to happen is yes, it becomes more efficient but we'll do more stuff because we're in competition so we'll spend exactly the same as we've always done, but just doing vastly more. But none the less, loads of consultants will write reports about how it will save you money and lots of people will be disappointed. >> I want to poke at that for a second. (laughing) I don't disagree with Javons Paradox when it comes to power, but example, say you know, our host for this event, A Cloud Guru. >> Yeah. >> They're priced to deliver per user is way lower than if they'd have done this the traditional way and I've heard many examples here at the show already where they've said, oh if I had built it this way, you know, it's now an order of magnitude less dollars, so. >> Let's forget order of mag, let's go many orders of magnitude. So from now to say the 1980s, for a thousand dollars, I can get a million times more compute resource than I could back then. Has my IT budget reduced a million fold during that time? And the answer is >> Yeah. >> What, my IT budget has reduced a million fold? >> No, no, no my IT budget has not reduced a million fold. >> Not at all, because we've just ended up doing vastly more stuff. >> Yeah, yeah. >> So the point is, yes. >> Budgets are always flat, yes. >> So the point is yes, we will be able to do the same things but more efficiently, but your IT budget doesn't reduce because we end up doing more things. So we're in competition, say, you and me and say you evolve, you use these environments you don't reduce your IT spending, you do more things, I'm now having to spend more and more just to try and keep up with you. So eventually I'm forced to adopt to that new world. So what happens is the individual acts become more efficient, but because we do more, we don't save anything. >> You know, want to look at kind of, maps versus strategy. >> Okay. >> I guess one of the things, if I'm talking to the typical Enterprise CIO or Board and they say, oh, well, a year ago I heard about Serverless, or today I heard about Serverless, you know, the strategy is going to change greatly because this is changing so rapidly, how do you help companies understand when things are changing so fast, how do I set a strategy for today? How long do I keep it? How often do I revisit it? >> So, if you map an environment, like all maps, they're dynamic, so you're constantly adapting and changing them as the environment is changing. So, when you look at, you have the purpose of your company, you have the landscape you're operating in, there are a number of climatic patents, about 30 of them, which impact that environment, will change it, so you need to understand those. Then there's sort of university useful patents known as doctrine, then there's game play. Now, for most organizations, because they cannot see the environment, they cannot distinguish, or may just be completely oblivious to any of this, so when they were talking about change, if I look at how things evolve from genesis, custom built product commodity, most organizations will go genesis, that's an innovation, every custom built feature differentiation of a product's an innovation, every shift in product to utility is an innovation, so all they see is innovation, innovation, innovation. And therefore, it's very easy to get sucked in to one size fits all methods work. One size innovation programs, where in fact, the genesis you would be using something like a lightweight XP, the product development, much more lean enterprise, so SCRUM and MVP and the utility is much more outsourcing or Six Sigma. So you should be using multiple techniques and multiple methods and most organizations aren't in that position. And if they're not in that position, of being able to see the environment, it's difficult to see where to attack, it's difficult to understand why here over there, it's difficult to manipulate the market. So, what happens is most organizations work on gut feel, whatever's popular in HPR and just act. And you can call that strategy if you wish. >> Alright, so I wish we could talk for another couple of hours, but want to give you the final take away >> Yes. >> Serverless today, how should people be thinking about it and what should they be looking for over the next six to 12 months in this space? >> So, the key thing about Serverless is we're seeing a shift from platform from product to utility, so you should be developing skills in that space. And we're seeing co-evolution of practice. By that, we mean there is a new set of practices combining finance and development together. What those practices are, we don't know yet. You have to experiment and explore. That's why attending events and being involved in building stuff will help you discover those practices. So today if your company, well it depends on your position, so if you're a company which is behind the game, you, say, haven't gone into infractructure as a service, you're not doing DevOps, you're own people are resistant to this change cause the other vendors say you're going to lose their jobs and blah, then rather then embarking on a five to seven year program, 'cause that's how long it will take to do that, you should move up the stack and start with Serverless and learning those practices. 'Cause no one knows them well, so you can take your people who've got inertia and re-train them in that space overcoming that inertia and give yourself a path forward. So, depends on your position, but I think most companies should be experimenting in this space. >> Alright, well Simon Wardley, it's a pleasure to catch up with you today. >> Delight. >> Hope to have you back on theCUBE at another event soon. Thank you so much for watching theCUBE.