>>Okay, welcome back everyone. Cube's coverage here. Live on the floor at AWS summit, 2022, an in person event in San Francisco. Of course, AWS summit, 2022 in New York city is coming up this summer. The cube will be there as well. Make sure you check us out then too, but we day two of coverage had a great guest here. I Han VP of developer relations, Mongo DB, formally of AWS. We've been known each other for a long time doing, uh, developer relations at Mongo DB. Welcome to the queue. Good to see >>You. Thank to be here. Thanks for inviting me, John. It's great >>To, so Mongo DB is, um, first of all, stocks' doing really well right now. Businesswise is good, but I still think it's undervalue. A lot of people think is, is a lot more going huge success with Atlas. So congratulations to the team over there. Um, what's the update? What's the relationship withs, you know, guys have been great partners for years. What's the new thing. Yeah. >>So MongoDB Atlas obviously runs on several different major cloud providers, but AWS is the largest partner that we work with in the public cloud. So the majority of our Atlas workloads for our customers are running on the AWS platform. And just earlier this year, we announced a new strategic collaboration agreement with AWS. That's gonna further strengthen and deepen that partnership that we have with them. >>What's the main product value right now on the scale on, on Atlas, what's the drive in the revenue momentum. >>So, I mean, you know, there's a huge trend in the industry towards cloud managed databases, right? You look back 10, 15 years ago when we first met, most customers were only and operating their own data infrastructure, either running it in their own data centers, or maybe if they were really early using the primitives that cloud providers like AWS offered to run their databases in the cloud when Amazon launched RDS back in 2009, I think it was, we started to see this trend towards cloud managed databases. We followed that with our own Atlas offering back in 2016. And as Andy jazzy from AWS would say very often it's offloading that UND differentiated, heavy lifting, allowing developers to focus on building applications. They don't have to win and operate the data infrastructure. We do it for them, and that has proven incredibly popular amongst our customers. You know, Atlas route right now is growing at 50, sorry, 85% car year on year growth. >>You know, um, I've been following MongoDB for a long, long time. I mean, going back to the lamp stack days, you know, and you think about what Mongo has done as a product because of the developer traction, you know, Mongo can't do this, just keeps getting better every year. And, and the, I think the stickiness with developers is a real big part of that. Can you your view there cuz you're in VE relations. I mean, developers all love Mongo. They're teaching in school. People are picking up a side hustles, they're coding on it, using it all everywhere. I mean it's well known. >>There's a few different reasons for that. I think the main one is the, the document orientated model that we use, the document data models that are used by Mongo DB, just a net way for developers to work with data. And then, uh, we've invested in creating 16 first party drivers that allow developers using various different programming languages, whether that's JavaScript or Python or rust to integrate MongoDB, natively and idiomatic with their software. So it's very, very easy for a developer to pick up MongoDB, grab one of these drivers from their package manager of their choice and then build applications that natively manipulate data inside MongoDB, whether that's MongoDB Atlas or our enterprise edition on their own premises. They get a very consistent and very easy to, I easy to use developer experience with our, with our platform. >>Talk about the go to market with AWS. You guys also have a tightly coupled relationships. There's been announcements there recently. Uh, what's changing most right now that people should pay attention to. Well, >>The first thing is there's a huge amount of technical integration between MongoDB and AWS services. And that's the basis for many of our customers choosing to run Mon Mongo DB on AWS. We're active in 23 AWS regions around the world. And there's many other integration points as well, like cryptographic protection of Mongo MongoDB, stored data using Amazon cryptographic services, for example, or building serverless applications with AWS Lambda and MongoDB servers. So there's a ton of technical integration. Yeah, but what we started to work on now is go to market integration with AWS as well. So you can buy Mongo DB Atlas through AWS's marketplace. You can use the payer, you go offering to pay for it with your AWS bill. And then we're collaborating with AWS on migrations and other joint go to market activities as well. That >>Means get incentives, the sales people at AWS. >>Of course our moreover I mean, it's just really easy for customers, really easy for developers to consume. Yeah, they don't need to contract with MongoDB. They can use their existing AWS contracting, their existing discounting relationships and pre purchasing arrangements with AWS to consume Atlas. >>It's the classic meet the customers where they >>Are exactly right. Meet the developer where they are and meet the customers where they are now with this new model as well. >>Yeah. I love marketplace. I think it's been great. You know, even with its kind of catalog and vibe, I think it's gonna get better and better, uh, over there teams doing good work. Um, and it's easy to consume. That's key. >>Yeah. Super easy. Reduce that friction and make it real easy for developers to adopt this. Right. >>Talk about some of the top customers that you guys share with AWS. What are some of the customers you guys have together and what the benefits of the >>Relationship joint references that we talk about? A lot, one of them is Shutterfly. So in the photographic products area, they built a eCommerce offering with MongoDB and AWS. The second is seven 11 with seven 11. We're doing a lot in the mobile space. So edge applications, we've got a feature in MongoDB Atlas that allows you to synchronize data with databases on mobile devices. Those can be phones point of sale devices or handheld devices that might be used in the parcel industry, for example. So seven 11 using us in that way. And then lastly with Pitney Bowes, we've got a big digital transformation project with Pitney Bowes where they've reimagined their, uh, postage and packaging services, delivering those to their customers, using MongoDB as a data store as well. >>I wanna get in some of the trends, you've got a great per you know, you know, Mongo from Amazon side and now you're there. Um, Mongo's, as you pointed out has, has been around for a long time. What are some of the stats? I mean, how many customers, how many countries? Well, it's pretty massive >>Mind. We've got almost quarter of a billion downloads today, 240 million MongoDB downloads since we launched the first product <laugh>, we've got 33,000 active customers that are using MongoDB Atlas today and we're running well over a million free tier clusters on MongoDB Atlas across all of the different providers where we operate the service as well. So these numbers are, you know, mind blowing in terms of scale. Uh, but of course at the core of that is operational excellence. Customers love Mongo DBS because they don't have to operate it themselves. They don't have to deal with fairly conditions. They don't have to deal with scaling. They don't have to deal with deployment. We all, we do all of those things as part of the service offering and customers get an endpoint that they can use with their applications to store and retrieve data reliably. And with consistently high perform, >>You know, it's, you know, in the media, something has to be dead. Someone's the death of the iPhone, the death of this, nothing that really dies. Mongo DB has always been kind of like talked about, well, it doesn't scale on the high end. Of course, Oracle was saying that, I mean, all the, all the big database vendors were kind of throwing darts at, at Mongo, uh, DB, uh, but it kept scaling. Atlas is a whole nother. Could you just unpack that a little bit more? Why is it so important? Because scale is just, I mean, it's, it's horizontal, but it's also performant. >>Exactly. Right. So with, uh, Mongo DB's document access model that I've described already, you break some of the limitations that exist inside traditional relational databases. So, you know, they don't scale well, if you've got high concurrent and see of data access, and they're typically difficult and expensive to scale because you need to share data. Once you grow beyond individual cluster nodes, and you'll know that all relational databases suffer from these same kinds of issues with non relational systems, no SQL systems like MongoDB, you have to think a little bit more about design at the beginning. So designing database to cater for the different access patterns that you have, but in return for that upfront preparation, that design work, you get near limitless, scalability and performance will scale nearly linearly with that scalability as well. So very much more high performance, very much more simplicity for the developer as their database gets larger and their cluster gets larger to support it. >>Yeah. You know, Amazon web service has always had an a and D jazz. We talk to us all the time, every interview I've done with Swami and Matt wood or whoever on the team and executive levels always said the same thing. There's not one database to rule the world, right? Obvious you're talking about Oracle, but even within AWS customers, they're mixing and matching databases based on use cases. So in distributed environment, they're all working together. So, um, you guys fit nicely into that. So how does that, >>I think strategy slightly counterbalances that so, you know, they would say use the specific tool for the specific task that you have in hand. Yeah. What we try to focus on is creating the simple and most effective developer experience that we can, and then supporting different facets to the product in order to allow developers to different use cases. A really good example with something like MongoDB Atlas search. So we integrated Apache Luine into MongoDB Atlas. Customers can very simply apply Apache Luine search indexes to the data that they've got in MongoDB. And then they can interact with that search data using the same drivers as an API. Yeah, yeah. That they use for regular queries. So if you want to run search on your application data, you don't need a separate open search or elastic search cluster, just turn on MongoDB Atlas search and use that, that search facet. So it's interest and we have other capabilities that it's >>Vertically integrating inside within Mongo, >>Correct? Yes. That's better. Yeah. With the guy, all of creating a really simple and effective developer experience, boosting developer productivity and helping developers get more done in less time. >>You mentioned serverless earlier, what's the serverless angle with AWS when Mongo, >>Is there one? Yeah. So we have MongoDB serverless currently in preview, uh, has the same kind of characteristics that you would, or the characteristics that you would expect from a serverless data base. So consumption based model, you provision an endpoint and that will scale elastically in accordance with your usage and you get billed by consumption units so much like the serverless paradigm that we've seen delivered by AWS, the same kind of model for Mongo, DB, Atlas serverless. >>What, what attracted you to Mongo DBS? So you knew them before, or you moved over there. Um, what's going on there? What's the culture like right now? Oh, >>The culture's great. I mean, it's a much smaller company than AWS where I was before, you know, it's a very large organization. And one of the things that I really like about MongoDB is, as I've said earlier, we can serve the different use cases that a developer might have with a single product, with different aspects, to it, different facets to it. Uh, and it's a really great conversation to have with a, with a developer, with a developer customer, to be able to offer one thing that helps them solve five or six different problems that have traditionally been quite hard for them to wrestle with quite difficult for them to, to deal with. And then we've got this focus on developer experience through these driver packages that we have as well. So it's really great to have as a developer relations pro have that kind of tooling in my kit bag that can help developers become more effective. >>Talk about tooling, cuz you know, I always have, uh, kind of moments where I waffle between more. I love platforms, tools are being over overused, too many tools tool with the tool, you know, the expressions, but we're seeing from developers, the ones that don't want to go into the hood, we serverless plays beautifully. Yep. They want tools. They do. And, and the, the new engineering developers that are coming outta college and universities, they love tools. >>Yeah. And we actually have quite a few of those built into Mongo, DB Atlas. So inside Mongo, DB Atlas, we've got things like an index optimizer, which will suggest the best way that you might index your data for better perform months inside MongoDB, running on Atlas, we've got a data Explorer, which is much like another product that we've got called MongoDB compass that allows you to see and manipulate the data that you have stored within your database natively within the Atlas interface. Uh, and then we also have, uh, whole slew of different metrics, monitoring capabilities built into the platform as well. So these are aspects of Atlas that developers can take advantage of. And then over on the client side, visual studio code plugins. Yeah. So you can manipulate and operate with data directly inside visual studio code, which is obviously the most common and popular IDE out there today, as well as integration with things like infrastructure is code tools. So we support cloud formation for provisioning. We have CDK constructs inside. Yeah. The CDK construct library. We also have a lot of customers using Terraform to provision MongoDB across both AWS and other providers. So having that developer tooling of course is super important. Yeah. Aspect of the developer experience, trying to >>Build out deploying observability is a big one. How does that fit in? Cuz you knew need to talk and not only measure everything here, but talk to other systems. >>Yeah. So we recently announced a provider for Prometheus and Grafana. So we can emit metrics into those providers. Obviously CNCF projects, very common and popular inside customers that are running on Kubernetes. We've got a Kubernetes operator for MongoDB Atlas as well. Good. So you can provision MongoDB Atlas from within Kubernetes as well as having our own native metrics directly within Atlas as well. >>Ian you're crushing it. You got all the, the data, the fingertips. Are you gonna be at Cuban this year? Uh, >>I will be, but some of our team members will definitely be there. >>Yeah, we'll be at, uh, EU. The cube will be there. Great. Thanks for coming on. Appreciate the insight final world. I'll give you the last word. Tell the audience what's going on. What's at Mongo DB. What should they pay attention to? If they've used Mongo and are aware of it? What's the update. What's >>The so you should come to MongoDB world actually in New York at the beginning of June, June 7th, the ninth in the Javit center in New York. Gonna have our own show there. And of course we'd love to see you there. >>Okay. Cube comes here day two of eight, us summit, 2020, this Cub I'm John for your host. Stay with us more. Our coverage as day two winds down. Great coverage.

(upbeat music) >> Hello, welcome to this CUBE conversation I'm John Furrier your host here in theCUBE in Palo Alto, California, featuring Cribl a hot startup taking over the enterprise when it comes to data pipelining, and we have a CUBE alumni who's the co-founder and CEO, Clint Sharp. Clint, great to see you again, you've been on theCUBE, you were on in 2013, great to see you, congratulations on the company that you co-founded, and leading as the chief executive officer over $200 million in funding, doing this really strong in the enterprise, congratulations thanks for joining us. >> Hey, thanks John it's really great to be back. >> You know, remember our first conversation the big data wave coming in, Hadoop World 2010, now the cloud comes in, and really the cloud native really takes data to a whole nother level. You've seeing the old data architectures being replaced with cloud scale. So the data landscape is interesting. You know, Data as Code you're hearing that term, data engineering teams are out there, data is everywhere, it's now part of how developers and companies are getting value whether it's real time, or coming out of data lakes, data is more pervasive than ever. Observability is a hot area, there's a zillion companies doing it, what are you guys doing? Where do you fit in the data landscape? >> Yeah, so what I say is that Cribl and our products and we solve the problem for our customers of the fundamental tension between data growth and budget. And so if you look at IDCs data data's growing at a 25%, CAGR, you're going to have two and a half times the amount of data in five years that you have today, and I talk to a lot of CIOs, I talk to a lot of CISOs, and the thing that I hear repeatedly is my budget is not growing at a 25% CAGR so fundamentally, how do I resolve this tension? We sell very specifically into the observability in security markets, we sell to technology professionals who are operating, you know, observability in security platforms like Splunk, or Elasticsearch, or Datadog, Exabeam, like these types of platforms they're moving, protocols like syslog, they're moving, they have lots of agents deployed on every endpoint and they're trying to figure out how to get the right data to the right place, and fundamentally you know, control cost. And we do that through our product called Stream which is what we call an observability pipeline. It allows you to take all this data, manipulate it in the stream and get it to the right place and fundamentally be able to connect all those things that maybe weren't originally intended to be connected. >> So I want to get into that new architecture if you don't mind, but let me first ask you on the problem space that you're in. So cloud native obviously instrumentating, instrumenting everything is a key thing. You mentioned data got all these tools, is the problem that there's been a sprawl of things being instrumented and they have to bring it together, or it's too costly to run all these point solutions and get it to work? What's the problem space that you're in? >> So I think customers have always been forced to make trade offs John. So the, hey I have volumes and volumes and volumes of data that's relevant to securing my enterprise, that's relevant to observing and understanding the behavior of my applications but there's never been an approach that allows me to really onboard all of that data. And so where we're coming at is giving them the tools to be able to, you know, filter out noise and waste, to be able to, you know, aggregate this high fidelity telemetry data. There's a lot of growing changes, you talk about cloud native, but digital transformation, you know, the pandemic itself and remote work all these are driving significantly greater data volumes, and vendors unsurprisingly haven't really been all that aligned to giving customers the tools in order to reshape that data, to filter out noise and waste because, you know, for many of them they're incentivized to get as much data into their platform as possible, whether that's aligned to the customer's interests or not. And so we saw an opportunity to come out and fundamentally as a customers-first company give them the tools that they need, in order to take back control of their data. >> I remember those conversations even going back six years ago the whole cloud scale, horizontally scalable applications, you're starting to see data now being stuck in the silos now to have high, good data you have to be observable, which means you got to be addressable. So you now have to have a horizontal data plane if you will. But then you get to the question of, okay, what data do I need at the right time? So is the Data as Code, data engineering discipline changing what new architectures are needed? What changes in the mind of the customer once they realize that they need this new way to pipe data and route data around, or make it available for certain applications? What are the key new changes? >> Yeah, so I think one of the things that we've been seeing in addition to the advent of the observability pipeline that allows you to connect all the things, is also the advent of an observability lake as well. Which is allowing people to store massively greater quantities of data, and also different types of data. So data that might not traditionally fit into a data warehouse, or might not traditionally fit into a data lake architecture, things like deployment artifacts, or things like packet captures. These are binary types of data that, you know, it's not designed to work in a database but yet they want to be able to ask questions like, hey, during the Log4Shell vulnerability, one of all my deployment artifacts actually had Log4j in it in an affected version. These are hard questions to answer in today's enterprise. Or they might need to go back to full fidelity packet capture data to try to understand that, you know, a malicious actor's movement throughout the enterprise. And we're not seeing, you know, we're seeing vendors who have great log indexing engines, and great time series databases, but really what people are looking for is the ability to store massive quantities of data, five times, 10 times more data than they're storing today, and they're doing that in places like AWSS3, or in Azure Blob Storage, and we're just now starting to see the advent of technologies we can help them query that data, and technologies that are generally more specifically focused at the type of persona that we sell to which is a security professional, or an IT professional who's trying to understand the behaviors of their applications, and we also find that, you know, general-purpose data processing technologies are great for the enterprise, but they're not working for the people who are running the enterprise, and that's why you're starting to see the concepts like observability pipelines and observability lakes emerge, because they're targeted at these people who have a very unique set of problems that are not being solved by the general-purpose data processing engines. >> It's interesting as you see the evolution of more data volume, more data gravity, then you have these specialty things that need to be engineered for the business. So sounds like observability lake and pipelining of the data, the data pipelining, or stream you call it, these are new things that they bolt into the architecture, right? Because they have business reasons to do it. What's driving that? Sounds like security is one of them. Are there others that are driving this behavior? >> Yeah, I mean it's the need to be able to observe applications and observe end-user behavior at a fine-grain detail. So, I mean I often use examples of like bank teller applications, or perhaps, you know, the app that you're using to, you know, I'm going to be flying in a couple of days. I'll be using their app to understand whether my flight's on time. Am I getting a good experience in that particular application? Answering the question of is Clint getting a good experience requires massive quantities of data, and your application and your service, you know, I'm going to sit there and look at, you know, American Airlines which I'm flying on Thursday, I'm going to be judging them based on off of my experience. I don't care what the average user's experience is I care what my experience is. And if I call them up and I say, hey, and especially for the enterprise usually this is much more for, you know, in-house applications and things like that. They call up their IT department and say, hey, this application is not working well, I don't know what's going on with it, and they can't answer the question of what was my individual experience, they're living with, you know, data that they can afford to store today. And so I think that's why you're starting to see the advent of these new architectures is because digital is so absolutely critical to every company's customer experience, that they're needing to be able to answer questions about an individual user's experience which requires significantly greater volumes of data, and because of significantly greater volumes of data, that requires entirely new approaches to aggregating that data, bringing the data in, and storing that data. >> Talk to me about enabling customer choice when it comes around controlling their data. You mentioned that before we came on camera that you guys are known for choice. How do you enable customer choice and control over their data? >> So I think one of the biggest problems I've seen in the industry over the last couple of decades is that vendors come to customers with hugely valuable products that make their lives better but it also requires them to maintain a relationship with that vendor in order to be able to continue to ask questions of that data. And so customers don't get a lot of optionality in these relationships. They sign multi-year agreements, they look to try to start another, they want to go try out another vendor, they want to add new technologies into their stack, and in order to do that they're often left with a choice of well, do I roll out like get another agent, do I go touch 10,000 computers, or a 100,000 computers in order to onboard this data? And what we have been able to offer them is the ability to reuse their existing deployed footprints of agents and their existing data collection technologies, to be able to use multiple tools and use the right tool for the right job, and really give them that choice, and not only give them the choice once, but with the concepts of things like the observability lake and replay, they can go back in time and say, you know what? I wanted to rehydrate all this data into a new tool, I'm no longer locked in to the way one vendor stores this, I can store this data in open formats and that's one of the coolest things about the observability late concept is that customers are no longer locked in to any particular vendor, the data is stored in open formats and so that gives them the choice to be able to go back later and choose any vendor, because they may want to do some AI or ML on that type of data and do some model training. They may want to be able to forward that data to a new cloud data warehouse, or try a different vendor for log search or a different vendor for time series data. And we're really giving them the choice and the tools to do that in a way in which was simply not possible before. >> You know you are bring up a point that's a big part of the upcoming AWS startup series Data as Code, the data engineering role has become so important and the word engineering is a key word in that, but there's not a lot of them, right? So like how many data engineers are there on the planet, and hopefully more will come in, come from these great programs in computer science but you got to engineer something but you're talking about developing on data, you're talking about doing replays and rehydrating, this is developing. So Data as Code is now a reality, how do you see Data as Code evolving from your perspective? Because it implies DevOps, Infrastructure as Code was DevOps, if Data as Code then you got DataOps, AIOps has been around for a while, what is Data as Code? And what does that mean to you Clint? >> I think for our customers, one, it means a number of I think sort of after-effects that maybe they have not yet been considering. One you mentioned which is it's hard to acquire that talent. I think it is also increasingly more critical that people who were working in jobs that used to be purely operational, are now being forced to learn, you know, developer centric tooling, things like GET, things like CI/CD pipelines. And that means that there's a lot of education that's going to have to happen because the vast majority of the people who have been doing things in the old way from the last 10 to 20 years, you know, they're going to have to get retrained and retooled. And I think that one is that's a huge opportunity for people who have that skillset, and I think that they will find that their compensation will be directly correlated to their ability to have those types of skills, but it also represents a massive opportunity for people who can catch this wave and find themselves in a place where they're going to have a significantly better career and more options available to them. >> Yeah and I've been thinking about what you just said about your customer environment having all these different things like Datadog and other agents. Those people that rolled those out can still work there, they don't have to rip and replace and then get new training on the new multiyear enterprise service agreement that some other vendor will sell them. You come in and it sounds like you're saying, hey, stay as you are, use Cribl, we'll have some data engineering capabilities for you, is that right? Is that? >> Yup, you got it. And I think one of the things that's a little bit different about our product and our market John, from kind of general-purpose data processing is for our users they often, they're often responsible for many tools and data engineering is not their full-time job, it's actually something they just need to do now, and so we've really built tool that's designed for your average security professional, your average IT professional, yes, we can utilize the same kind of DataOps techniques that you've been talking about, CI/CD pipelines, GITOps, that sort of stuff, but you don't have to, and if you're really just already familiar with administering a Datadog or a Splunk, you can get started with our product really easily, and it is designed to be able to be approachable to anybody with that type of skillset. >> It's interesting you, when you're talking you've remind me of the big wave that was coming, it's still here, shift left meant security from the beginning. What do you do with data shift up, right, down? Like what do you, what does that mean? Because what you're getting at here is that if you're a developer, you have to deal with data but you don't have to be a data engineer but you can be, right? So we're getting in this new world. Security had that same problem. Had to wait for that group to do things, creating tension on the CI/CD pipelining, so the developers who are building apps had to wait. Now you got shift left, what is data, what's the equivalent of the data version of shift left? >> Yeah so we're actually doing this right now. We just announced a new product a week ago called Cribl Edge. And this is enabling us to move processing of this data rather than doing it centrally in the stream to actually push this processing out to the edge, and to utilize a lot of unused capacity that you're already paying AWS, or paying Azure for, or maybe in your own data center, and utilize that capacity to do the processing rather than having to centralize and aggregate all of this data. So I think we're going to see a really interesting, and left from our side is towards the origination point rather than anything else, and that allows us to really unlock a lot of unused capacity and continue to drive the kind of cost down to make more data addressable back to the original thing we talked about the tension between data growth, if we want to offer more capacity to people, if we want to be able to answer more questions, we need to be able to cost-effectively query a lot more data. >> You guys had great success in the enterprise with what you got going on. Obviously the funding is just the scoreboard for that. You got good growth, what are the use cases, or what's the customer look like that's working for you where you're winning, or maybe said differently what pain points are out there the customer might be feeling right now that Cribl could fit in and solve? How would you describe that ideal persona, or environment, or problem, that the customer may have that they say, man, Cribl's a perfect fit? >> Yeah, this is a person who's working on tooling. So they administer a Splunk, or an Elastic, or a Datadog, they may be in a network operations center, a security operation center, they are struggling to get data into their tools, they're always at capacity, their tools always at the redline, they really wish they could do more for the business. They're kind of tired of being this department of no where everybody comes to them and says, "hey, can I get this data in?" And they're like, "I wish, but you know, we're all out of capacity, and you know, we have, we wish we could help you but we frankly can't right now." We help them by routing that data to multiple locations, we help them control costs by eliminating noise and waste, and we've been very successful at that in, you know, logos, like, you know, like a Shutterfly, or a, blanking on names, but we've been very successful in the enterprise, that's not great, and we continue to be successful with major logos inside of government, inside of banking, telco, et cetera. >> So basically it used to be the old hyperscalers, the ones with the data full problem, now everyone's got the, they're full of data and they got to really expand capacity and have more agility and more engineering around contributions of the business sounds like that's what you guys are solving. >> Yup and hopefully we help them do a little bit more with less. And I think that's a key problem for our enterprises, is that there's always a limit on the number of human resources that they have available at their disposal, which is why we try to make the software as easy to use as possible, and make it as widely applicable to those IT and security professionals who are, you know, kind of your run-of-the-mill tools administrator, our product is very approachable for them. >> Clint great to see you on theCUBE here, thanks for coming on. Quick plug for the company, you guys looking for hiring, what's going on? Give a quick update, take 30 seconds to give a plug. >> Yeah, absolutely. We are absolutely hiring cribl.io/jobs, we need people in every function from sales, to marketing, to engineering, to back office, GNA, HR, et cetera. So please check out our job site. If you are interested it in learning more you can go to cribl.io. We've got some great online sandboxes there which will help you educate yourself on the product, our documentation is freely available, you can sign up for up to a terabyte a day on our cloud, go to cribl.cloud and sign up free today. The product's easily accessible, and if you'd like to speak with us we'd love to have you in our community, and you can join the community from cribl.io as well. >> All right, Clint Sharp co-founder and CEO of Cribl, thanks for coming to theCUBE. Great to see you, I'm John Furrier your host thanks for watching. (upbeat music)

>> Live from Las Vegas. It's theCUBE. Covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel and their ecosystem partners. >> And welcome back to our continuing coverage here on theCUBE of AWS re:Invent, we're on day three of three days of wall to wall coverage that we've brought you here from the Sands Expo along with David Vellante, I'm John Walls. Glad you're with us here, we're joined by David Flynn from Hammerspace, and David, good afternoon to you. >> Good afternoon. >> Been quite a year for you, right? >> Yeah. >> This has been something else. Set us up a little bit about where you've been, the journey you're on right now with Hammerspace and maybe for folks at home who aren't familiar, a little bit about what you do. >> So Hammerspace is all about data agility. We believe that data should be like the air you breathe, where you need it, when you need it, without having to think about it. Today, data's managed by copying it between the sundry different types of storage. And that's 'cause we're managing data through the storage system itself. What we want is for data to simply be there, when you need it. So it's all about data agility. >> I need to know more. So let's talk about some of your past endeavors. Fusion-io we watched you grow that company from just an idea. You solved the block storage problem, you solved the performance problems, amazing what you guys did with that company. My understanding is you're focused on file. >> That's right. >> Which is a much larger-- >> Unstructured data in general file and object. >> So a much larger proportion of the data that's out there. >> Yes. >> What's the problem that you guys are going after? >> Well at Fusion-io and this was pre-flash, now flash everybody takes it for granted. When we started it didn't really exist in the data center. And if you're using SAN, most likely it's for performance. And there's a better way to get performance with flash down in the server. Very successful with that. Now the problem is, people want the ease of managablility of having a global name space of file and object name space. And that's what we're tackling now because file is not native in the Cloud. It's kind of an afterthought. And all of these different forms of storage represents silos into which you copy data, from on-prem into cloud, between the different types of storage, from one site to another. This is what we're addressing with virtualizing the data, putting powerful metadata in control of how that data's realized across multiple data centers across the different types of storage, so that you see it as a single piece of data regardless of where it lives. >> Okay so file's not a first class citizen. You're making copies, moving data all over the place. You got copy creep going on. >> It's like cutting off Hydra's head. When you manage data by copying it you're just making more of it and that's because the metadata's down with the data. Every time you make a copy, it's a new piece of data that needs to be managed. >> So talk more about the metadata structure, architecture, what you guys are envisioning? >> Fundamentally, the technology is a separate metadata control plane that is powerful enough to present data as both file and object. And takes that powerful metadata, and puts it in control of where the data is realized, both in terms of what data center it's in, as well as what type of storage it's on, allowing you to tap into the full dynamic range of the performance of server-attached flash, of course Fusion-io, very near and dear to my heart, getting tens of millions of I-ops and tens of gigabytes per second, you can't do that across the network. You have to have the data be very agile, and be able to be promoted into the server. And then be able to manage it all the way to global scale between whole different data centers. So that's the magic of being able to cover the full dynamic range performance to capacity, scale and distance, and have it be that same piece of data that's simply instantiated, where you need it, when you need it, based on the power of the metadata. >> So when you talk about object, you talk about a simplified means of interacting, it's a get-put paradigm right? >> That's right. >> So that's something that you're checking up? >> That's right, ultimately you need to also have random read and write semantics and very high performance, and today, the standard model is you put your data in object storage and then you have your application rewritten to pull it down, store it on some local storage, to work with it and then put it back. And that's great for very large-scale applications, where you can invest the effort to rewrite them. But what about the world where they want the convenience of, the data is simply there, in something that you can mount as a file system or access as object, and it can be at the highest performance of random IO against local flash, all the way to cold in the Cloud where it's cheap. >> I get it so it's like great for Shutterfly 'cause they've got the resources to rewrite the application but for everybody else. >> That's right, and that's why the web scalers pioneered the notion of object storage and we helped them with the local block to get very, very high performance. So that bifurcated world, because the spectrum got stretched so wide that a single size fits all no longer works. So you have to kind of take object on the capacity, distance and scale side, and block, local on the performance side. But what I realized early on, all the way back to Fusion-io is that it is possible to have a shared namespace, both file system and object, that can span that whole spectrum. But to do that you have to provide really powerful metadata as a separate service that has the competency to actually manage the realization of the data across the infrastructure. >> You know David you talk about data agility, so that's what we're all about right? We're all about being agile. Just conceptually today, a lot more data than you've ever had to deal with before. In a lot more places. >> It's a veritable forest. >> With a lot more demands, so just fundamentally, how do you secure that agility. How can you provide that kind of reliability and agility, in that environment, like the challenge for you. >> Oh yeah. Well the challenge really goes back to the fact that the network storage protocols haven't had innovation for like 20 years because of the world of NAS being so dominant by a few players, well one. There really hasn't been a lot of innovation. Y'know NFSv3 three has been around for decades. NFSv4 didn't really happen. It was slower and worse off. At the heart of the storage networking protocols for presenting a file system, it hadn't even been enhanced to be able to communicate across hostile networks. So how are you going to use that at the kind of scale and distance of cloud, right? So what I did, after leaving Fusion-io, was I went and teamed up with the world's top experts. We're talking here about Trent Micklebus, the Linux Kernel author and maintainer of the storage networking stack. And we have spent the last five plus years fixing the fundamental plumbing that makes it possible to bring the shared file semantic into something that becomes cloud native. And that really is two things. One is about the ability to scale, both performance, capacity, in the metadata and in the data. And you couldn't do that before because NAS systems fundamentally have the metadata and data together. Splitting the two allows you to scale them both. So scale is one. Also the ability to secure it over large distances and networks, the ability to operate in an eventually consistent, to work across multiple datacenters. NAS had never made the multi-datacenter leap. Or the securing it across other networks, it just hadn't got there. But that is actually secondary compared to the fact that the world of NAS is very focused on the infrastructure guys and the storage admin. And what you have to do is elevate the discussion to be about the data user and empower them with powerful metadata to do self service. And as a service so that they can completely automate all of the concerns about the infrastructure. 'Cause if there's anything that's cloud, it's being able to delegate and hand off the infrastructure concerns, and you simply can't do that when you're focused at it from a storage administration and data janitorial kind of model. >> So I want to pause for a second and just talk to our audience and just stress how important it is to pay attention to this man. So there's no such thing as a sure thing in business. But there is one sure thing that is if David Flynn's involved you're going to disrupt something so you disrupted Scuzzy, the horrible storage stack. So when you hear things today like NVME and CAPPY and Atomic Rights and storage class memory, you got it all started. Fusion-io. >> That's right. >> And that was your vision that really got that started up. When I used to talk to people about that they would say I'm crazy, and you educated myself and Floyer and now you see it coming to fruition today. So you're taking aim at decades old infrastructure and protocols called NAS, and trying to do the same thing at Cloud scale, which is obviously something you know a lot about. >> That's right. I mean if you think about it. The spectrum of data, goes from performance on the one hand to ease of manageability, distance and scale, cost capacity versus cost performance. And that's inherent to our physical universe because it takes time to propagate information to a distance and to get ease of manageability to encode things very, very tight to get capacity efficiency, takes time, which works against performance. And as technology advances the spectrum only gets wider, and that's why we're stuck to the point of having to bifurcate it, that performance is locally attached flash. And that's what I pioneered with flash in the server in NVME. I told everybody, EMC, SAN, it sucks. If you want performance put flash in the server. Now we're saying if you want ease of use and manageability there's a better way to do that than NAS, and even object storage. It's to separate the metadata as a distinct control plane that is put in charge of managing data through very rich and powerful metadata, and that puts the data owner in control of their data. Not just across different types of storage in the performance capacity spectrum, but also across on-prem and in the Cloud, and across multi-cloud. 'Cause the Cloud after all is just another big storage silo. And given the inertia of data, they've got you by the balls when they've got all the data there. (laughing) I'm sorry, I know I'm at AWS I should be careful what I say. >> Well this is live. >> Yeah, okay so they can't censor us, right. So just like the storage vendors of yesteryear, would charge you an arm and a leg when their arrays were out of service, to get out of your service, because they knew that if you were trying to extend the service life of that, that that's because it was really hard for you to get the data off of it because you had to suffer application downtime and all of that. In the same fashion, when you have your data in the Cloud, the egress costs are so expensive. And so this is all about putting the data owner in control of the data by giving them a rich powerful metadata platform to do that. >> You always want to have strategies that give you flexibility, exit strategies if things don't work out, so that's fascinating. I know we got to wrap, but give us the low-down on the company, the funding, what can you share with us. Go-to-market, et cetera. >> So it's a tightly held company. I was very successful financially. So from that point of view we're... >> Self-funded. >> Self-funded, funded from angels. I made some friends with Fusion-io right? So from that point of view yeah, it's the highest power team you can get. I mean these are great guys, the Linux Kernel maintainer on the storage networking stack. This was a heavy lift because you have to fix the fundamental plumbing in the way storage networking works so that you can, it's like a directories service for data, and then all the management service. This has been a while in the making, but it's that foundational engineering. >> You love heavy lifts. >> I love hard problems. >> I feel like I mis-introduced you, I should have said the great disruptor is what I should have said. >> Well, we'll see. I think disrupting the performance side was a pure play and very easy. Disrupting the ease of use side of the data spectrum, that's the fun one that's actually so transformative because it touches the people that use the data. >> Well best of luck. It was really, I'm excited for ya. >> Thanks for joining us David. Appreciate the time. David Flynn joined up from Hammerspace, and back with more on theCUBE at AWS re:Invent. (upbeat music)

welcome back to pre owned alive Jeff Rick here with the cube as you know we go out to the signals we we go out to the offense we extract the signal from the noise or date to hear percona live Santa Clara Convention Center the heart of Silicon Valley John had to step away so I'll be going solo on this and we're excited to to invite to the cube Lane Campbell CEO and co-founder of Blackbird welcome to the cube thank you very much so Blackbird is a new name I saw on my notes what was what was it called before well we are a merger of two companies Palomino DB has been a longtime sponsor and contributor at at Kona for about seven years it has focused on MySQL database operations and consulting dr dev was an operation shop with a DevOps focus okay and we've decided to merge together take everything up the stack build a company that could operate everything with a heavy database focus awesome so when did you complete the merger probably thirty years from now but technically we did in January first okay very good congratulations never never that fun to to complete all the other processes behind a merger absolutely good deal so we caught you I guess in between two keynotes here mmm-hmm at the show mhm so when he tell us a little bit about what you're covering earlier and what are you gonna cover in the not-too-distant future as soon as you get to your slides after we finish the interview absolutely I'm doing a melange of Amazon Web Services talks this time so I just finished scaling MySQL and Amazon Web Services or I talked about both options of Amazon's RDS and ec2 opportunities and the next session is a deep dive into RDS so the relational database service okay great so we were just at at Amazon summit last week in San Francisco we're at Amazon reinvent last year will be at Amazon some in New York City in a couple of months I think July and then of course back at reinvent in October so clearly Amazon has changed in the world that cloud service has been completely transformative and the enterprise disruptive everyone's running to to catch the Andy Jesse and the team at the show just released it just you know it's like an avalanche of feature improvements feature improvements as the breadth of services gets wider and then the depth of the services gets deeper and then I think they announced their forty third consecutive price decrease yes at the show so there's just relentless innovation both in terms of the feature set as well as the as the as the pricing pressure so how did you get involved on working on the Amazon side and what are you seeing in the marketplace with some of your customers and how is it transforming absolutely we started with Amazon when clients were going to it and it was obviously something we need to support particularly we've always been a very bespoke cost company we do make sure to support our customers but like Amazon we can't do everything so Amazon will start with a core and then they'll evolve based on customer need they'll start digging out new features new functionality and so we did the same thing and as more customers used Amazon we moved to Amazon as more customers use RDS we started using RDS and yeah at this point I would say about 75% of our customers are in some sort of cloud whether it is Amazon Google compute Rackspace cloud and even some folks who are building their own private clouds as well and realistically the own that's the way it's gonna go in a few years everything if every piece of infrastructure will be abstracted and this isn't a really exciting time to be part of the move towards that as we evolve our own maturity matrix for customers to show them where they stand on the DevOps maturity Bay matrix being in a virtualized environment where one can evolve very agile configuration management and infrastructure as code is crucial and so we have that's what we at this point we're helping a lot of our customers get to that point we're helping a lot of our customers not need operation staff and managing everything ourselves which is much easier in a virtual cloud environment and also letting people know when it's not the right choice for them so so on the Amazon side right they have the service of yours your value-add then is helping customers is it a configuration piece is it how they set it up is it what apps are they using I mean where where's your value-add sit on top of the Amazon infrastructure then they're purchasing directly from Amazon so Amazon themselves are utility that's all they want to be and they're not interested in running systems that sit on their environment and so we will help customers from a strategic view deciding which which in which a virtualized environment whether it's Amazon or something else is the right choice we will help them choose which of their architectural components should use an Amazon service versus their own service that they would run anywhere and once we do that we help people migrate to Amazon and we can run it the whole thing okay so you help them run it absolutely yes then are you guys playing an OpenStack as well we do have a few customers in OpenStack it's growing a combat side little earlier but yes absolutely so talk a little bit about when when customers are talking about making the move to the cloud and they want to use Amazon or they want to use a service like that what are some of the strategic gates you walked in through and making a decision as to whit you know what should be where what workloads should be in a public cloud what workload should be maybe on their own or behind the firewall or you know where a hybrid is more appropriate absolutely and I will say that up until recently we have predominantly worked with startups who are about in their mid level of maturity so not as much enterprise clients who might have much more hybridized environment realistically a lot of the folks that come in don't have large operations staff they don't and the staff that they do have want to be working on features right what we call development velocity and so we look for customers who recognize that and item a at this point I don't think a virtualized environment is optional anymore and more often than not unless they are an enterprise or unless they have a large commitment to an existing data center going with something like open stock doesn't make a lot of sense but that being said we do make sure with anyone that we are bringing in that we set everything up with a mitigated risk so that it is easy to get them out even though we've never had an issue with any specific provider for risk purposes it makes a lot of sense to use multiple clouds or to use an on-premise and other hybrid so then so that their startups or most of the applications that you're getting involved with their new applications that they're building as part of their startup a game or whatever one if you can give any examples so we're very much in their retail vertical and the gaming vertical we do have a few others in healthcare and you know sometimes I tease sometimes infrastructure but predominantly and most of the verticals we work with are either retail or gaming and in those environments we will either be brought in for a system that has grown past often that's already either already in Amazon but it was not architected for scale okay and we will come in and help them get to that next level okay more often than not we do have of course some green fields we're doing a large large infrastructure change right now for a new acquisition for Shutterfly okay and in that environment we're going right to RDS and using that okay so one of the one of the potential knocks on a cloud environment or infrastructures of service is is is there a point in time where the cost of rent suddenly becomes more than it would be the cost to buy we're often for speed of implementation getting started clearly renting a service is the easier and lower friction do you find that with your customers or as Amazon able to keep up in terms of pricing reductions where they can stay where they tend to stay kind of Amazon pure as opposed to hitting you know kind of this breaking point where maybe we really should put in our own infrastructure and it's getting really expensive to continue to kind of rent the service absolutely in RDS there was a there was a point where people were getting priced out of RDS which is more expensive than the instances underneath and at that point we had a lot of customers coming to us asking to move the new PI think they dropped most of their prices and RDS by 40% last week so it's amazing right so it gets a lot better some of the larger systems can be very significant but at this point you can get a managed database server that is fully redundant for about six thousand dollars a year and it's pretty impressive what we will find is we'll help customers manage cost one of the things people forget is you have a whole new component of infrastructure management in how do you whether it's using reserved instances spot instances auto scaling up and auto scaling down removing snapshots there's so many opportunities to manage costs that people forget about and we make sure that that happens as well so that people don't get runaway kraut runaway bills so to really find really fine-tune their their their instance at AWS or kind of cost optimize based on because there's a lot of choices right there's a lot of there's a lot of variables in an Amazon in a lot of Amazon purchase yes and there are absolutely tons of ways to save money it's essentially just another facet of automation becomes the cost management part of it and that's one of the most amazing things of Amazon is particularly for a customer that can leverage elasticity whether it's because of peak seasons retail during Christmas education during semesters any customer that can rely on the Dyna Missa tee of an Amazon can scale up can scale down can shift out and really pay when they need to pay or not pay when they don't okay so you've been doing this for a while from kind of a longer-term perspective right there's a lot of new entrants into the public cloud space really you know Google compute and you know Cisco just announced a billion-dollar initiative I think last week for their new public cloud you got HP cloud but sure there's a lot of clouds out there mmm but clearly it appears that anglin's got a giant lead I think Andy said it was their eighth year of the AWS summit what's your kind of perspective as a kind of a service provider looking at the market and trying to deliver value to your customers as to Amazon's position relative to everybody else kind of jumping in the game so at this point we predominantly work with either Amazon Google compute or Rackspace and that is where we focused we don't do a significant amount of Windows so we haven't really played too much with Azure at this point we are predominantly working with what our customers already have if it is completely Greenfield which it's pretty rare they'll bring in a service provider that early we would tend to focus on a combination of those two and that of course will depend on the strategy and the goal we don't want to over build something before they actually have the revenue and the business model supporting what they need there's a lot of options out there like anything it's a matter of managing risk and as a I am a CEO but I was a database administrator by trade and managing risk is core so I will not go to a new database release in its first year and I will not go to a new cloud and probably its first three to four years unless there's something extraordinarily compelling feature that just makes you be willing to accept a huge amount of risk right okay so let's shift gears a little bit and talk about we're here at Percona live shows growing I think he said it's his tenth year of the show why is this important event what's the what's the feeling you're getting here at the show from the community so I started coming to these back when they was in our Riley show when it was the O'Reilly of MySQL conference versus percona who took it over open source is a huge deal and it still is extraordinarily relevant I believe very firmly that open source technology and the access to code the access to tech and to software and the access to open source education is what's going to help us get into the next level of the technological workforce at this point I'm not sure you probably know the numbers since I know you do this more than me but even in Silicon Valley there are 300,000 Latino families who don't have access to computers and internet so any any come any organization like percona liven like MySQL that is based on open source needs to be supported because that is going to be what helps a child in Kenya solve cancer figure out cancer and get us to the next level so that's why I come out here yeah we support closed source databases too but wherever possible we're going to come support an open source product so let's shift gears again cuz I know you're passionate about diversity in tech and you've talked about some of the digital divide you know with with families and people having access to the to the tools and then of course the education and and and the focus on stem we're big fans of women in tech and diversity in tech all of us have we don't have a lot of women hosts but we all have a lot of daughters yeah we're pretty passionate about it and growing up here in the heart of the valley clearly girls need to learn how to code mom so can you talk about some of the things that you get involved with to support that effort in terms of diversity in tech absolutely one one amazing incident actually is at percona live last year they did not have a code of conduct and we had a bit of an issue and some there was a some conversations had and this year we're gonna live now has a code of conduct which helps women come out and feel like there's a clearly written statement that they will not be harassed they will not be intimidated that they are welcome and that is a huge step in and of itself and it was really an issue last year in the year 20 2013 there always is there always is it's amazing when you actually start looking at women speaking out about harassment and you know even abuse at conferences how it quickly devolves into them being attacked stalked harassed it's pretty radical so I was very happy that rakonin took that on and got that in place I was on the content committee for this conference and I was in the beginning there were only about five five proposals out of 400 from women and they were really very nice about helping me extend it and get out there and get more women presenting at the conference here which is great I'm speaking at a bright role hosted data-driven Women events in about a month and wherever I can getting out there at the ghats he just invited me to code his craft to talk about that at their meetups as well good that's he's an amazing organization for bringing women into tap good it seems to be getting more exposure so just a shot out four we've got a great women in tech playlist of women in tech that have been on the cube if you go to Silicon angle dot TV look under playlist women in tech I think we just looked before we came on there we have 97 women of all roles responsibilities seniority size of companies who've been on the cube and you'll be joining that list shortly X so we're big fans and and it's it's it is amazing in 2014 that this is still an issue but we do see more and more at these conferences that there's often you know kind of a women in tech launch track or special networking event or or thanks to really encourage two women to be not only involved but really kind of take a leadership position we saw that back with at EMC world last year with Sheryl Sandberg as well so that's that's great so what's kind of next you've been doing this a long time you've been involving this community a while what's kind of the next big hill to take in terms of the micing community well right now for us it's DevOps and I don't know if you're familiar with it but near this culture of bringing the development operations teams together as we have more infrastructure as code as we get to a point where you cannot compete if you cannot continually push code out push change out that's where we reached and with every customer we're working on we're pushing development velocity getting them to have you know the ability to push code out as fat as rapidly as they won and as safely as they want we just announced today an open-source toolkit for continuous delivery for databases that is starting with MySQL and we feel like that's going to be the next step big data of course is there we are in the middle of ramping up a cassandra team which is a very good addition in the data ecosystem to a relational system like like MySQL and the demand for it is insane so we're very excited to have just brought on our second full time experience because Andre DBA and a building that out as well so in the clients right there's a lot of huge trends right now there's there's kind of mobile first right it was to recently get the mobile first as a driver there's the DevOps culture and and agile software development you know just get stuff out in this this continual pace of improvements and bug fixes and rolling and then and then finally the data first mm-hmm which is kind of the newer trend within your clients of those three things what's really the the primary driver if you had to pick one of the three I will answer that in a way that doesn't answer your question but that happens often excellent right now I believe it's DevOps in a few years and no one will know what that is anymore it will be ubiquitous it is an opportunity right now and then it's going to be data at this point you know we're in the cloud environment and it is the next revolution this virtualized environment infrastructure as a utility just like the electrical and industrial revolutions but data really is a big data and you know how does how to get the data in right now we're in the basics how do you get all of that data in there how do you keep it available how do you manage these huge forms of data but soon it will be about the machine learning and the continued evolution of pulling insights from it and that's what we're gonna be seeing awesome Elaine thanks for coming on the cube Thank You V been here with Len Campbell the CEO and co-founder of Blackbird we're at percona live 2014 Santa Clara California you're watching the cube we go out to the events extract the signal from the noise get the smartest people that we can find in the room bring them on the cube ask them the questions you'd like to ask them so thanks for staying with us we'll be back after this short break with our next guest