hi everybody welcome back to re invent 2022. this is thecube's exclusive coverage we're here at the satellite set it's up on the fifth floor of the Venetian Conference Center and this is part of the global startup program the AWS startup showcase series that we've been running all through last year and and into this year with AWS and featuring some of its its Global Partners Ed wallson series the CEO of chaos search many times Cube Alum and Kevin Miller there's also a cube Alum vice president GM of S3 at AWS guys good to see you again yeah great to see you Dave hi Kevin this is we call this our Super Bowl so this must be like your I don't know uh World Cup it's a pretty big event yeah it's the World Cup for sure yeah so a lot of S3 talk you know I mean that's what got us all started in 2006 so absolutely what's new in S3 yeah it's been a great show we've had a number of really interesting launches over the last few weeks and a few at the show as well so you know we've been really focused on helping customers that are running Mass scale data Lakes including you know whether it's structured or unstructured data we actually announced just a few just an hour ago I think it was a new capability to give customers cross-account access points for sharing data securely with other parts of the organization and that's something that we'd heard from customers is as they are growing and have more data sets and they're looking to to get more out of their data they are increasingly looking to enable multiple teams across their businesses to access those data sets securely and that's what we provide with cross-count access points we also launched yesterday our multi-region access point failover capabilities and so again this is where customers have data sets and they're using multiple regions for certain critical workloads they're now able to to use that to fail to control the failover between different regions in AWS and then one other launch I would just highlight is some improvements we made to storage lens which is our really a very novel and you need capability to help customers really understand what storage they have where who's accessing it when it's being accessed and we added a bunch of new metrics storage lens has been pretty exciting for a lot of customers in fact we looked at the data and saw that customers who have adopted storage lens typically within six months they saved more than six times what they had invested in turning storage lens on and certainly in this environment right now we have a lot of customers who are it's pretty top of mind they're looking for ways to optimize their their costs in the cloud and take some of those savings and be able to reinvest them in new innovation so pretty exciting with the storage lens launch I think what's interesting about S3 is that you know pre-cloud Object Store was this kind of a niche right and then of course you guys announced you know S3 in 2006 as I said and okay great you know cheap and deep storage simple get put now the conversations about how to enable value from from data absolutely analytics and it's just a whole new world and Ed you've talked many times I love the term yeah we built chaos search on the on the shoulders of giants right and so the under underlying that is S3 but the value that you can build on top of that has been key and I don't think we've talked about his shoulders and Giants but we've talked about how we literally you know we have a big Vision right so hard to kind of solve the challenge to analytics at scale we really focus on the you know the you know Big Data coming environment get analytics so we talk about the on the shoulders Giants obviously Isaac Newton's you know metaphor of I learned from everything before and we layer on top so really when you talk about all the things come from S3 like I just smile because like we picked it up naturally we went all in an S3 and this is where I think you're going Dave but everyone is so let's just cut the chase like so any of the data platforms you're using S3 is what you're building but we did it a little bit differently so at first people using a cold storage like you said and then they ETL it up into a different platforms for analytics of different sorts now people are using it closer they're doing caching layers and cashing out and they're that's where but that's where the attributes of a scale or reliability are what we did is we actually make S3 a database so literally we have no persistence outside that three and that kind of comes in so it's working really well with clients because most of the thing is we pick up all these attributes of scale reliability and it shows up in the clients environments and so when you launch all these new scalable things we just see it like our clients constantly comment like one of our biggest customers fintech in uh Europe they go to Black Friday again black Friday's not one days and they lose scale from what is it 58 terabytes a day and they're going up to 187 terabytes a day and we don't Flinch they say how do you do that well we built our platform on S3 as long as you can stream it to S3 so they're saying I can't overrun S3 and it's a natural play so it's it's really nice that but we take out those attributes but same thing that's why we're able to you know help clients get you know really you know Equifax is a good example maybe they're able to consolidate 12 their divisions on one platform we couldn't have done that without the scale and the performance of what you can get S3 but also they saved 90 I'm able to do that but that's really because the only persistence is S3 and what you guys are delivering but and then we really for focus on shoulders Giants we're doing on top of that innovating on top of your platforms and bringing that out so things like you know we have a unique data representation that makes it easy to ingest this data because it's kind of coming at you four v's of big data we allow you to do that make it performant on s3h so now you're doing hot analytics on S3 as if it's just a native database in memory but there's no memory SSC caching and then multi-model once you get it there don't move it leverage it in place so you know elasticsearch access you know Cabana grafana access or SQL access with your tools so we're seeing that constantly but we always talk about on the shoulders of giants but even this week I get comments from our customers like how did you do that and most of it is because we built on top of what you guys provided so it's really working out pretty well and you know we talk a lot about digital transformation of course we had the pleasure sitting down with Adam solipski prior John Furrier flew to Seattle sits down his annual one-on-one with the AWS CEO which is kind of cool yeah it was it's good it's like study for the test you know and uh and so but but one of the interesting things he said was you know we're one of our challenges going forward is is how do we go Beyond digital transformation into business transformation like okay well that's that's interesting I was talking to a customer today AWS customer and obviously others because they're 100 year old company and they're basically their business was they call them like the Uber for for servicing appliances when your Appliance breaks you got to get a person to serve it a service if it's out of warranty you know these guys do that so they got to basically have a you know a network of technicians yeah and they gotta deal with the customers no phone right so they had a completely you know that was a business transformation right they're becoming you know everybody says they're coming a software company but they're building it of course yeah right on the cloud so wonder if you guys could each talk about what's what you're seeing in terms of changing not only in the sort of I.T and the digital transformation but also the business transformation yeah I know I I 100 agree that I think business transformation is probably that one of the top themes I'm hearing from customers of all sizes right now even in this environment I think customers are looking for what can I do to drive top line or you know improve bottom line or just improve my customer experience and really you know sort of have that effect where I'm helping customers get more done and you know it is it is very tricky because to do that successfully the customers that are doing that successfully I think are really getting into the lines of businesses and figuring out you know it's probably a different skill set possibly a different culture different norms and practices and process and so it's it's a lot more than just a like you said a lot more than just the technology involved but when it you know we sort of liquidate it down into the data that's where absolutely we see that as a critical function for lines of businesses to become more comfortable first off knowing what data sets they have what data they they could access but possibly aren't today and then starting to tap into those data sources and then as as that progresses figuring out how to share and collaborate with data sets across a company to you know to correlate across those data sets and and drive more insights and then as all that's being done of course it's important to measure the results and be able to really see is this what what effect is this having and proving that effect and certainly I've seen plenty of customers be able to show you know this is a percentage increase in top or bottom line and uh so that pattern is playing out a lot and actually a lot of how we think about where we're going with S3 is related to how do we make it easier for customers to to do everything that I just described to have to understand what data they have to make it accessible and you know it's great to have such a great ecosystem of partners that are then building on top of that and innovating to help customers connect really directly with the businesses that they're running and driving those insights well and customers are hours today one of the things I loved that Adam said he said where Amazon is strategically very very patient but tactically we're really impatient and the customers out there like how are you going to help me increase Revenue how are you going to help me cut costs you know we were talking about how off off camera how you know software can actually help do that yeah it's deflationary I love the quote right so software's deflationary as costs come up how do you go drive it also free up the team and you nail it it's like okay everyone wants to save money but they're not putting off these projects in fact the digital transformation or the business it's actually moving forward but they're getting a little bit bigger but everyone's looking for creative ways to look at their architecture and it becomes larger larger we talked about a couple of those examples but like even like uh things like observability they want to give this tool set this data to all the developers all their sres same data to all the security team and then to do that they need to find a way an architect should do that scale and save money simultaneously so we see constantly people who are pairing us up with some of these larger firms like uh or like keep your data dog keep your Splunk use us to reduce the cost that one and one is actually cheaper than what you have but then they use it either to save money we're saving 50 to 80 hard dollars but more importantly to free up your team from the toil and then they they turn around and make that budget neutral and then allowed to get the same tools to more people across the org because they're sometimes constrained of getting the access to everyone explain that a little bit more let's say I got a Splunk or data dog I'm sifting through you know logs how exactly do you help so it's pretty simple I'll use dad dog example so let's say using data dog preservability so it's just your developers your sres managing environments all these platforms are really good at being a monitoring alerting type of tool what they're not necessarily great at is keeping the data for longer periods like the log data the bigger data that's where we're strong what you see is like a data dog let's say you're using it for a minister for to keep 30 days of logs which is not enough like let's say you're running environment you're finding that performance issue you kind of want to look to last quarter in last month in or maybe last Black Friday so 30 days is not enough but will charge you two eighty two dollars and eighty cents a gigabyte don't focus on just 280 and then if you just turn the knob and keep seven days but keep two years of data on us which is on S3 it goes down to 22 cents plus our list price of 80 cents goes to a dollar two compared to 280. so here's the thing what they're able to do is just turn a knob get more data we do an integration so you can go right from data dog or grafana directly into our platform so the user doesn't see it but they save money A lot of times they don't just save the money now they use that to go fund and get data dog to a lot more people make sense so it's a creativity they're looking at it and they're looking at tools we see the same thing with a grafana if you look at the whole grafana play which is hey you can't put it in one place but put Prometheus for metrics or traces we fit well with logs but they're using that to bring down their costs because a lot of this data just really bogs down these applications the alerting monitoring are good at small data they're not good at the big data which is what we're really good at and then the one and one is actually less than you paid for the one so it and it works pretty well so things are really unpredictable right now in the economy you know during the pandemic we've sort of lockdown and then the stock market went crazy we're like okay it's going to end it's going to end and then it looked like it was going to end and then it you know but last year it reinvented just just in that sweet spot before Omicron so we we tucked it in which which was awesome right it was a great great event we really really missed one physical reinvent you know which was very rare so that's cool but I've called it the slingshot economy it feels like you know you're driving down the highway and you got to hit the brakes and then all of a sudden you're going okay we're through it Oh no you're gonna hit the brakes again yeah so it's very very hard to predict and I was listening to jassy this morning he was talking about yeah consumers they're still spending but what they're doing is they're they're shopping for more features they might be you know buying a TV that's less expensive you know more value for the money so okay so hopefully the consumer spending will get us out of this but you don't really know you know and I don't yeah you know we don't seem to have the algorithms we've never been through something like this before so what are you guys seeing in terms of customer Behavior given that uncertainty well one thing I would highlight that I think particularly going back to what we were just talking about as far as business and digital transformation I think some customers are still appreciating the fact that where you know yesterday you may have had to to buy some Capital put out some capital and commit to something for a large upfront expenditure is that you know today the value of being able to experiment and scale up and then most importantly scale down and dynamically based on is the experiment working out am I seeing real value from it and doing that on a time scale of a day or a week or a few months that is so important right now because again it gets to I am looking for a ways to innovate and to drive Top Line growth but I I can't commit to a multi-year sort of uh set of costs to to do that so and I think plenty of customers are finding that even a few months of experimentation gives them some really valuable insight as far as is this going to be successful or not and so I think that again just of course with S3 and storage from day one we've been elastic pay for what you use if you're not using the storage you don't get charged for it and I think that particularly right now having the applications and the rest of the ecosystem around the storage and the data be able to scale up and scale down is is just ever more important and when people see that like typically they're looking to do more with it so if they find you usually find these little Department projects but they see a way to actually move faster and save money I think it is a mix of those two they're looking to expand it which can be a nightmare for sales Cycles because they take longer but people are looking well why don't you leverage this and go across division so we do see people trying to leverage it because they're still I don't think digital transformation is slowing down but a lot more to be honest a lot more approvals at this point for everything it is you know Adam and another great quote in his in his keynote he said if you want to save money the Cloud's a place to do it absolutely and I read an article recently and I was looking through and I said this is the first time you know AWS has ever seen a downturn because the cloud was too early back then I'm like you weren't paying attention in 2008 because that was the first major inflection point for cloud adoption where CFO said okay stop the capex we're going to Opex and you saw the cloud take off and then 2010 started this you know amazing cycle that we really haven't seen anything like it where they were doubling down in Investments and they were real hardcore investment it wasn't like 1998 99 was all just going out the door for no clear reason yeah so that Foundation is now in place and I think it makes a lot of sense and it could be here for for a while where people are saying Hey I want to optimize and I'm going to do that on the cloud yeah no I mean I've obviously I certainly agree with Adam's quote I think really that's been in aws's DNA from from day one right is that ability to scale costs with with the actual consumption and paying for what you use and I think that you know certainly moments like now are ones that can really motivate change in an organization in a way that might not have been as palatable when it just it didn't feel like it was as necessary yeah all right we got to go give you a last word uh I think it's been a great event I love all your announcements I think this is wonderful uh it's been a great show I love uh in fact how many people are here at reinvent north of 50 000. yeah I mean I feel like it was it's as big if not bigger than 2019. people have said ah 2019 was a record when you count out all the professors I don't know it feels it feels as big if not bigger so there's great energy yeah it's quite amazing and uh and we're thrilled to be part of it guys thanks for coming on thecube again really appreciate it face to face all right thank you for watching this is Dave vellante for the cube your leader in Enterprise and emerging Tech coverage we'll be right back foreign

(gentle music) >> Now welcome back to theCUBE, everyone. I'm John Walls, and once again, we're glad to have you here for AWS re:Invent 22. Our coverage continues here on Thursday, day three, of what has been a jam-packed week of tech and AWS, of course, has been the great host for this. It's now a pleasure to welcome in Anurag Gupta, who is the founder and CEO of Shoreline, joining us here as part of the AWS Global Showcase Startup Program, and Anurag, good to see you, sir. Thanks for joining us. >> Thank you so much. >> Tell us about Shoreline, about what you're up to. >> So we're a DevOps company. We're really focused on repairing issues. If you think about it, there are a ton DevOps companies and we all went to the cloud in order to gain faster innovation and by and large check. Then all of the things involved in getting things into production, artifact generation, testing, configuration management, deployment, also by and large, automated. Now pity the poor SRE who's getting the deluge of stuff on them, every week, every two days, sometimes multiple times a day, and it's complicated, right? Kubernetes, VMs, lots of services, multiple clouds, sometimes, and you know, they need to know a little bit about everything. And you know what, there are a ton of companies that actually help you with what we call Day-2 Ops. It's just that most of them help you with observability, telling you what's gone wrong, or incident management, routing something to someone. But you know, back when I was at AWS, I never got really that excited about one more dashboard to look at or one more like better ticket routing. What used to really excite me was having some issue extinguished forever. And if you think about it, like the first five minutes of an incident are detecting and routing. The next hour, two hours, is some human being going in and fixing it, so that feels like the big opportunity to reduce, so hopefully we can talk a little bit about different ways that one can do that. >> What about Day-2 Ops? Just tell me about how you define that. >> So I basically define it as once the software goes into a production, just making sure things stay up and are healthy and you're resilient and you don't get errors and all of those sorts of things because everything breaks sooner or later, you know, to a greater or lesser degree. >> Especially that SRE you're talking about, right? >> Yeah. >> So let's go back to that scenario. Yeah, you pity the poor soul because they do have to be a little expert in everything. >> Exactly. >> And that's really challenging and we all know that, that's really hard. So how do you go about trying to lighten that burden, then? >> So when you look at the numbers, about somewhere between 40% to even 95% of the alarms that fire, the alerts that fire, are false positives and that's crazy. Why is someone waking up just to deal with? >> It's a lot of wasted time, isn't it? >> A lot of wasted time. And you know, you're also training someone into what I call ClickOps, just to go in and click the button and resolve it and you don't actually know if it was the false positive or it's the rare real positive, and so that's a challenge, right? And so the first thing to do is to figure out where the false positives are. Like, let's say Datadog tells you that CPU is high and alarms. Is that a good thing or a bad thing? It's hard for them to tell, right? But you have to then introspect it into something precise like, oh, CPU is high, but response times are standard and the request rate is high. Okay, that's a good thing. I'm going to ignore this. Or CPU is high, but it kind of resolves itself, so I'm going to not wake anybody up. Or CPU is high and oh, it's the darn JVM starting to garbage collect again, so let me go and take a heap dump and give that to my dev team and then bounce the JVM and you know, without waking anybody up, or CPU is high, I have no idea what's going on. Now it's time to wake somebody up. You know, what you want to use humans for is the ability to think about novel stuff, not to do repetitive stuff, so that's the first step. The second step is, about 40% of what remains is repetitive and straightforward. So like a disk is full, I'd better clean up the garbage on the disk or maybe grow the disk. People shouldn't wake up to deal to grow a disk. And so for that, what you want to do is just have those sorts of things get automated away. One of the nice things about Shoreline is, is that we take the experience in what we build for one company, and if they're willing, provide it to everybody else. Our belief is, a central tenant is, if someone somewhere fixes something, everyone everywhere should gain the benefit because we all sit on the same three clouds, we all sit on the same set of database infrastructure, et cetera. We should all get the same benefits. Why do we have to scar our own backs rather than benefiting from somebody else's scar tissue, so that's the second thing. The third thing is, okay, let's say it's not straightforward, not something I've seen before, then in that case, what often happens is on average like eight people get involved. You know, it initially goes to L1 support or L1 ops and, but they don't necessarily know because, as you say, the environment's complex. And so, you know, they go into Slack and they say, "At here, can somebody help me with this?" And those things take a much longer time, so wouldn't it be better that if your best SRE is able to say, "Hey, check these 20 things and then run these actions." We could convert that into like a Jupyter Notebook where you could say the incident got fired I pre-populated all the diagnostics, and then I tell people very precisely, "If you see this, run this, et cetera." Like a wiki, but actually something you could run right in this product. And then, you know, last piece of the puzzle, the smaller piece, is sometimes new things happen and when something new happens, what you want is sort of the central tech of Shoreline, which is parallel distributed, real-time debugging. And so the ability to do, you know, execute a command across your fleet rather than individual boxes so that you can say something like, "I'm hearing that my credit card app is slow. For everything tagged as being part of my credit card app, please run for everything that's running over 90% CPU, please run a top command." And so, you know, then you can run in the same time on one host as you can on 30,000 and that helps a lot. So that's the core of what we do. People use us for all sorts of things, also preventative maintenance, you know, just the proactive regular things. You know, like your car, you do an oil change, well, you know, you need to rotate your certs, certificates. You need to make sure that, you know, there isn't drift in your configurations, there isn't drift in your software. There's also security elements to it, right? You want to make sure that you aren't getting weird inbound/outbound traffic across to ports you don't expect to be open. You don't want to have these processes running, you know, maybe something's bad. And so that's all the kind of weird anomaly detection that's easy to do if you run things in a distributed parallel way across everything. That's super hard to do if you have to go and Whac-A-Mole across one box after the next. >> Well, which leads to a question just in terms of setting priorities then, which is what you're talking about helping companies establish priorities, this hierarchy of level one warning, level two, level three, level four. Sounds like that should be a basic, right? But you're saying that's not, that's not really happening in the enterprise. >> Well, you know, I would say that if you hadn't automated deployments, you should do that first. If you haven't automated your testing pipeline, shame on you, you should do that like a year ago. But now it's time to help people in production because you've done that other work and people are suffering. You know, the crazy thing about the cloud is, is that companies spend about three times more on the human beings to operate their cloud infrastructure as on the cloud infrastructure itself. I've yet to hear anybody say that their cloud bill is too low, you know, so, you know, there's a clearer savings also available. And you know, back when I was at AWS, obviously I had to keep the lights on too, but you know, I had to do that, but it's kind of a tax on my engineers and I'd really spend, prefer to spend the head count on innovation, on doing things that delight my customers. You never delight your customers by keeping the lights on, you just avoid irritating them by turning 'em off, right? >> So why are companies so fixed in on spending so much time on manually repairing things and not looking for these kinds of little, much more elegant solution and cost-efficient, time-saving, so on so forth. >> Yeah, I think there just hasn't been very much in this space as yet because it's a hard, hard problem to solve. You know, automation's a little bit scary and that's the reality of it and the way you make it less scary is by proving it out, by doing the simple things first, like reducing the alert fatigue, you know, that's easy. You know, providing notebooks to people so that they can click things and do things in a straightforward way. That's pretty easy. The full automation, that's kind of the North Star, that's what we aspire to do. But you know, people get there over time and one of our customers had 700 instances of this particular incident solved for them last week. You imagine how many human beings would've been doing it otherwise, you know? >> Right. >> That's just one thing, you know? >> How many did it take the build a pyramid? How many decades did that take, right? You had an announcement this week. I don't think we've talked about that. >> No, yeah, so we just announced Incident Insights, which is a free product that lets people plug into initially PagerDuty and pretty soon the Opsgenie ServiceNow, et cetera. And what you can do is, is you give us an API key read-only and we will suck your PagerDuty data out. We apply some lightweight ML unsupervised learning, and in a couple of minutes, we categorize all of your incidents so that you can understand which are the ones that happen most often and are getting resolved really quickly. That's ClickOps, right? Those alarms shouldn't fire. Which are the ones that involve a lot of people? Those are good candidates to build a notebook. Which are the ones that happen again and again and again? Those are good candidates for automation. And so, I think one of the challenges people have is, is that they don't actually know what their teams are doing and so this is intended to provide them that visibility. One of our very first customers was doing the beta test for us on it. He used to tell us he had about 100 tickets, incidents a week. You know, he brought this tool in and he had 2,100 last week and was all, you know, like these false alarms, so while he's giving us- >> That was eye opening for him to see that, sure. >> And why he's, you know, looking at it, you know, he's just like filing Jiras to say, "Oh, change this threshold, cancel this alarm forever." You know, all of that kind of stuff. Before you get to do the fancy work, you got to clean your room before you get to do anything else, right? >> Right, right, dinner before dessert, basically. >> There you go. >> Hey, thanks for the insights on this and again the name of the new product, by the way, is... >> Incident Insights. >> Incident Insights. >> Totally free. >> Free. >> Yeah, it takes a couple of minutes to set up. Go to the website, Shoreline.io/insight and you can be up and running in a couple of minutes. >> Outstanding, again, the company is Shoreline. This is Anurag Gupta, and thank you for being with us. We appreciate it. >> Appreciate it, thank you. >> Glad to have to here on theCUBE. Back with more from AWA re:Invent 22. You're watching theCUBE, the leader in high-tech coverage. (gentle music)

well hello everybody John Wallace here on thecube he's continuing our segments here on the AWS Global startup showcase we are at day three of Reinventing irking Zhang is joining us now he is the CEO co-founder of Jupiter one um first off before we get going talking about you know security and big world for you guys I know what's your take on the show what's been going on out here at re invent yeah yeah ring event has been one of my favorite shows there's a lot of people here there's a lot of topics of course it's not just cyber security a lot of cloud infrastructure and just technology in general so you get a lot you know if you go walk the floor you see a lot of vendors you look at us go into sessions you can learn a lot but you're the Hot Topic right everybody's focused on Cyber yeah big time and with good reason right because as we know the Bad actors are getting even smarter and even faster and even more Nimble so just paint the landscape for me here in general right now as you see uh security Cloud Security in particular and and kind of where we are in that battle well we are clearly not winning so I think that in itself is a bit of a uh interesting problem right so as a it's not just Cloud security if you think about cyber security in general as an industry it has it has not been around for that long right but if you just look at the history of it uh we haven't done that while so uh pick another industry say medicine which has been around forever and if you look at the history of Medicine well I would argue you has done tremendously well because people live longer right when you get sick you get access to health care and yeah exactly you have Solutions and and you can see the trend even though there are problems in healthcare of course right but the trend is is good it's going well but not in cyber security more breaches more attacks more attackers we don't know what the hell we're doing with that many solutions and you know that's been one of my struggles as a former CSO and security practitioner for many years you know why is it that we're not getting better all right so I'm going to ask you the question yeah okay why aren't we getting better you know how come we can't stay ahead of the curve on this thing that for some reason it's like whack-a-mole times a hundred every time we think we solve one problem we have a hundred more that show up over here exactly and we have to address that and and our attention keeps floating around yeah I think you said it right so because we're taking this guacamole approach and we're looking for the painkiller of the day and you know we're looking for uh the Band-Aids right so and then we ended up well I I think to be fair to be fair to your industry the industry moves so quickly technology in general moves so quickly and security has been playing catch-up over time we're still playing catch-up so when you're playing catch-up you you can almost only uh look at you know what's the painkiller of what's the band name of the day so I can stop the bleeding right but I do think that we're we're to a point or we have enough painkillers and Band-Aids and and we need to start looking at how can we do better fundamentally with the basics and do the basics well because a lot of times the basics that get you into trouble so fundamentally the foundation I if I hear you right what you're saying is um you know quick changing industry right things are moving rapidly but we're not blocking and tackling we're not doing the X's and O's and so forget changing and we we got to get back to the basis and do those things right exactly you can only seem so simple it seems so simple but it's so hard right so you can you can think about you know uh even in case of building a starter building a company and and in order at one point right so we're blocking uh blocking tackling and then when we grow to a certain size we have to scale we have to figure out how to scale the business this is the same problem that happens in security as an industry we've been blocking happening for so long you know we're the industry is so young but we're to a point that we got to figure out how to scale this scale this in a fundamentally different way and I'll give you some example right so so what when we say the basics now it's easy to to think that say users should have MFA enabled is one of the basics right or another Basics will be you have endpoint protection on your devices you know maybe it's Cloud strike or Sentinel one or carbon black or whatever but the question being how do you know it is working 100 of the time right how do you know that how do you know right you find out too exactly that's right and how do you know that you have 100 coverage on your endpoints those Solutions are not going to tell you because they don't know what they don't know right if it's not enabled if it's not you know what what's the negative that you are not seeing so that's one of the things that you know that's in the basic state that you're now covering so the fundamentals it really goes to these five questions that I think that nobody has a really good answer for until now so the five questions goes what do I have right is it important what's important out of all the things I have you have a lot right you could have millions of things what important now for those that are important does it have a problem and if it has a problem who can fix it because the reality is in most cases security teams are not the ones fixing the problems they're they're the ones identical they're very good at recognizing but not so good exactly identifying the owner who can fix it right right could be could be business owner could be Engineers so the the asset ownership identification right so so these four questions and and then over time you know whether it's over a week or a month or a quarter or a year am I getting better right and then you just keep asking these questions in different areas in different domains with a different lens right so maybe that's endpoints maybe that's Cloud maybe that's you know users maybe that's a product and applications right but it really boils down to these five questions that's the foundation for any good security program if you can do that well I think we cover a lot of bases and we're going to be in much better shape than we have been all right so where do you come in man Jupiter one in terms of what you're providing because obviously you've identified this kind of pyramid yes this hierarchy of addressing needs and I assume obviously knowing you as I do and knowing the company as I do you've got Solutions that's exactly right right and and we precisely answer those five questions right for uh any organization uh from a asset perspective right because all the the answers to all those these five questions are based in assets it starts with knowing what I have right right so the the overall challenge of cyber security being broke broken I I believe is fundamentally that people do not understand and cannot uh probably deal with the complexity that we have within our own environments so again like you know using uh medicine as an example right so in order to come up with the right medicine for either it's a vaccine for covid-19 or whether it is a treatment for cancer or whatever that case may be you have to start with the foundations of understanding both the pathogen and to the human body like DNA sequencing right without those you cannot effectively produce the right medicine in modern uh you know Medicine sure right so that is the same thing that's happening in cyber security you know we spend a lot of times you know putting band days in patches right and then we spend a lot of time doing attacker research from the outside but we don't fundamentally understand in a complete way what's the complexity within our own environment in terms of digital assets and that's that's almost like the DNA of your own work what is that kind of mind-blowing in a way that if again hearing you what you're talking about is saying that the first step is to identify what you have that's right so it seems just so basic that that I should know what I what's under my hood I should know what is valuable and what is not I should prioritize what I really need to protect and what maybe can go on the second shelf yeah it has been a tough problem since the beginning of I.T not just the beginning of cyber security right so in the history of I.T we have this thing called cmdb configuration management database it is supposed to capture the configurations of it assets now over time that has become a lot more complex and and there's a lot more than just it asset that we have to understand from a security and attack service perspective right so we have to understand I.T environments we have to understand Cloud environments and applications and users and access and data and as and all of those things then then we have to take a different approach of sort of a modern cmdb right so what is the way that we can understand all of those complexity within all of those assets but not just independently within those silos but rather in a connected way so we can not only understand the attack surface but only but also understand the attack path that connect the dots from one thing to another right because everything in the organization is actually connected if if there's any one thing that sits on an island right so if you say you have a a a a server or a device or a user that is on an island that is not connected to the rest of the organization then why have it right and it doesn't matter so it's the understanding of that connect connected tissue this entire map where this you know DNA sequencing equivalent of a digital organization is what Jupiter one provides right so that visibility of the fundamental you know very granular uh level of assets and resources to answer those five questions and how does that how do I get better at that then I mean I have you to help me but but internally within our organization um I mean I don't want to be rude but I mean do I have do I have the skill for that do I have um do I have the the internal horsepower for that or or is there some need to close that Gap and how do I do it you know I'll tell you two things right so so one you mentioned the worst skills right so let me start there so because this one is very interesting we also have a huge skills shortage in cyber security we will we've all heard that for years and and and and for a long time but if you dig deeper into it why is that why is that and you know we have a lot of you know talented people right so why do we still have a skills shortage now what's interesting is if you think about what we're asking security people to do is mind-boggling so if you if you get a security analyst to say hey I want to understand how to protect something or or how to deal with an incident and what you're asking the person to do is not only to understand the security concept and be a domain expert in security you're also asking the person to and understand at the same time AWS or other clouds or endpoints or code or applications so that you can properly do the analysis and the in the response it's it's impossible it's like you know if you have you have to have a person who's an expert in everything know everything about everything that's right it's impossible so so so that's that's one thing that we have to to resolve is how do we use technology like Jupiter one to provide an abstraction so that there's Automation in place to help the security teams be better at their jobs without having to be an expert in deep technology right just add the abstract level of understanding because you know we can we can model the data and and provide the analysis and visual visualization out of the box for them so they can focus on just the security practices so that's one and the second thing is we have to change the mindset like take vulnerability management as an example right so the mindset for vulnerability management has been how do I manage findings now we have to change it to the concept of more proactive and how to manage assets so let's think about uh you know say log4j right that that happened and uh you know when it happened everybody scrambles and said hey which which devices or which you know uh systems have log4j and you know it doesn't matter what's the impact we can fix it right going back to those questions that that I mentioned before right and then um and then they try to look for a solution at a time say well where's that silver bullet that can give me the answers now what what what we struggle with though is that you know I want to maybe ask the question where were you six months ago where were you six months ago where you could have done the due diligence and put something in place that help you understand all of these assets and connections so you can go to one place and just ask for that question when something like that you know hit the fan so so if we do not fundamentally change the mindset to say I have to look at things not from a reactive findings perspective but really starting from an asset-centric you know day one perspective to look at that and have this Foundation have this map build we can't get there right so it's like you know if I need direction I go to Google Maps right but the the reason that it works is because somebody has done the work of creating the map right right if you haven't if you don't have the map and you just at you know when the time you say I gotta go somewhere and you expect the map to magically happen to show you the direction it's not going to work right right I imagine there are a lot of people out there right now are listening to thinking oh boy you know and that's what Jupiter one's all about they're there to answer your oh boy thanks for the time of course I appreciate the insights as well it's nice to know that uh at least somebody is reminding us to keep the front door locked too that's just the back door the side doors keep that front door and that garage locked up too definitely um all right we'll continue our coverage here at AWS re invent 22 this is part of the AWS Global startup showcase and you're watching the cube the leader in high-tech coverage foreign

>>Well, hello everybody. John Walls here and continuing our coverage here at AWS Reinvent 22 on the queue. We continue our segments here in the Global Startup program, which of course is sponsored by AWS Startup Showcase, and with us to talk about any scale as the co-founder and CEO of the company, Robert and n, you are Robert. Good to see you. Thanks for joining us. >>Yeah, great. And thank you. >>You bet. Yeah. Glad to have you aboard here. So let's talk about Annie Scale, first off, for those at home and might not be familiar with what you do. Yeah. Because you've only been around for a short period of time, you're telling me >>Company's about >>Three years now. Three >>Years old, >>Yeah. Yeah. So tell us all about it. Yeah, >>Absolutely. So one of the biggest things happening in computing right now is the proliferation of ai. AI is just spreading throughout every industry has the potential to transform every industry. But the thing about doing AI is that it's incredibly computationally intensive. So if you wanna do do ai, you're not, you're probably not just doing it on your laptop, you're doing it across many machines, many gpu, many compute resources, and that's incredibly hard to do. It requires a lot of software engineering expertise, a lot of infrastructure expertise, a lot of cloud computing expertise to build the software infrastructure and distributed systems to really scale AI across all of the, across the cloud. And to do it in a way where you're really getting value out of ai. And so that is the, the problem statement that AI has tremendous potential. It's incredibly hard to do because of the, the scale required. >>And what we are building at any scale is really trying to make that easy. So trying to get to the point where, as a developer, if you know how to program on your laptop, then if you know how to program saying Python on your laptop, then that's enough, right? Then you can do ai, you can get value out of it, you can scale it, you can build the kinds of, you know, incredibly powerful applica AI applications that companies like Google and, and Facebook and others can build. But you don't have to learn about all of the distributed systems and infrastructure. It just, you know, we'll handle that for you. So that's, if we're successful, you know, that's what we're trying to achieve here. >>Yeah. What, what makes AI so hard to work with? I mean, you talk about the complexity. Yeah. A lot of moving parts. I mean, literally moving parts, but, but what is it in, in your mind that, that gets people's eyes spinning a little bit when they, they look at great potential. Yeah. But also they look at the downside of maybe having to work your way through Pike mere of sorts. >>So, so the potential is definitely there, but it's important to remember that a lot of AI initiatives fail. Like a lot of initiative AI initiatives, something like 80 or 90% don't make it out of, you know, the research or prototyping phase and inter production. Hmm. So, some of the things that are hard about AI and the reasons that AI initiatives can fail, one is the scale required, you know, moving. It's one thing to develop something on your laptop, it's another thing to run it across thousands of machines. So that's scale, right? Another is the transition from development and prototyping to production. Those are very different, have very different requirements. Absolutely. A lot of times it's different teams within a company. They have different tech stacks, different software they're using. You know, we hear companies say that when they move from develop, you know, once they prototype and develop a model, it could take six to 12 weeks to get that model in production. >>And that often involves rewriting a lot of code and handing it off to another team. So the transition from development to production is, is a big challenge. So the scale, the development to production handoff. And then lastly, a big challenge is around flexibility. So AI's a fast moving field, you see new developments, new algorithms, new models coming out all the time. And a lot of teams we work with, you know, they've, they've built infrastructure. They're using products out there to do ai, but they've found that it's sort of locking them into rigid workflows or specific tools, and they don't have the flexibility to adopt new algorithms or new strategies or approaches as they're being developed as they come out. And so they, but their developers want the flexibility to use the latest tools, the latest strategies. And so those are some of the main problems we see. It's really like, how do you scale scalability? How do you move easily from development and production and back? And how do you remain flexible? How do you adapt and, and use the best tools that are coming out? And so those are, yeah, just those are and often reasons that people start to use Ray, which is our open source project in any scale, which is our, our product. So tell >>Me about Ray, right? Yeah. Opensource project. I think you said you worked on it >>At Berkeley. That's right. Yeah. So before this company, I did a PhD in machine learning at Berkeley. And one of the challenges that we were running into ourselves, we were trying to do machine learning. We actually weren't infrastructure or distributed systems people, but we found ourselves in order to do machine learning, we found ourselves building all sorts of tools, ad hoc tools and systems to scale the machine learning, to be able to run it in a reasonable amount of time and to be able to leverage the compute that we needed. And it wasn't just us people all across, you know, machine learning researchers, machine learning practitioners were building their own tooling and infrastructure. And that was one of the things that we felt was really holding back progress. And so that's how we slowly and kind of gradually got into saying, Hey, we could build better tools here. >>We could build, we could try to make this easier to do so that all of these people don't have to build their own infrastructure. They can focus on the actual machine learning applications that they're trying to build. And so we started, Ray started this open source project for basically scaling Python applications and scaling machine learning applications. And, well, initially we were running around Berkeley trying to get all of our friends to try it out and, and adopt it and, you know, and give us feedback. And if it didn't work, we would debug it right away. And that slow, you know, that gradually turned into more companies starting to adopt it, bigger teams starting to adopt it, external contributors starting to, to contribute back to the open source project and make it better. And, you know, before you know it, we were hosting meetups, giving to talks, running tutorials, and the project was just taking off. And so that's a big part of what we continue to develop today at any scale, is like really fostering this open source community, growing the open source user base, making sure Ray is just the best way to scale Python applications and, and machine learning applications. >>So, so this was a graduate school project That's right. You say on, on your way to getting your doctorate and now you commercializing now, right? Yeah. I mean, so you're being able to offer it, first off, what a journey that was, right? I mean, who would've thought Absolutely. I guess you probably did think that at some point, but >>No, you know, when we started, when we were working on Ray, we actually didn't anticipate becoming a company, or we at least just weren't looking that far ahead. We were really excited about solving this problem of making distributed computing easy, you know, getting to the point where developers just don't have to learn about infrastructure and distributed systems, but get all the benefits. And of course, it wasn't until, you know, later on as we were graduating from Berkeley and we wanted to continue really taking this project further and, and really solving this problem that it, we realized it made sense to start a company. >>So help me out, like, like what, what, and I might have missed this, so I apologize if I did, but in terms of, of Ray's that building block and essential for your, your ML or AI work down the road, you know, what, what is it doing for me or what, what will it allow me to do in either one of those realms that I, I can't do now? >>Yeah. And so, so like why use Ray versus not using Ray? Yeah, I think the, the answer is that you, you know, if you're doing ai, you need to scale. It's becoming, if you don't find that to be the case today, you probably will tomorrow, you know, or the day after that. And so it's really increasingly, it's a requirement. It's not an option. And so if you're scaling, if you're trying to build these scalable applications you are building, you're either going to use Ray or, or something like Ray or you're going to build the infrastructure yourself and building the infrastructure yourself, that's a long journey. >>So why take that on, right? >>And many of the companies we work with don't want to be in the business of building and managing infrastructure. No. Because, you know, if they, they want their their best engineers to build their product, right? To, to get their product to market faster. >>I want, I want you to do that for me. >>Right? Exactly. And so, you know, we can really accelerate what these teams can do and, you know, and if we can make the infrastructure something they just don't have to think about, that's, that's why you would choose to use Ray. >>Okay. You know, between a and I and ml are, are they different animals in terms of what you're trying to get done or what Ray can do? >>Yeah, and actually I should say like, it's not just, you know, teams that are new teams that are starting out, that are using Ray, many companies that have built, already built their own infrastructure will then switch to using Ray. And to give you a few examples, like Uber runs all their deep learning on Ray, okay. And, you know, open ai, which is really at the frontier of training large models and, and you know, pushing the boundaries of, of ai, they train their largest models using Ray. You know, companies like Shopify rebuilt their entire machine learning platform using Ray, >>But they started somewhere else. >>They had, this is all, you know, like, it's not like the v1, you know, of their, of their machine learning infrastructure. This is like, they did it a different way before, this is like the second version or the third iteration of of, of how they're doing it. And they realize often it's because, you know, I mean in the case of, of Uber, just to give you one example, they built a system called hova for scaling deep learning on a bunch of GPUs. Right Now, as you scale deep learning on GPUs for them, the bottleneck shifted away from, you know, as you scale GPU's training, the bottleneck shifted away from training and to the data ingest and pre-processing. And they wanted to scale data ingest and pre-processing on CPUs. So now Hova, it's a deep learning framework. It doesn't do the data ingest and pre-processing on CPUs, but you can, if you run Hova on top of Ray, you can scale training on GPUs. >>And then Ray has another library called Ray Data you can, that lets you scale the ingest and pre-processing on CPUs. You can pipeline them together. And that allowed them to train larger models on more data before, just to take one example, ETA prediction, if you get in an Uber, it tells you what time you're supposed to arrive. Sure. That uses a deep learning model called d eta. And before they were able to train on about two weeks worth of data. Now, you know, using Ray and for scaling the data, ingestive pre-processing and training, they can train on much more data. You know, you can get more accurate ETA predictions. So that's just one example of the kind of benefit they were able to get. Right. Also, because it's running on top of, of Ray and Ray has this ecosystem of libraries, you know, they can also use Ray's hyper parameter tuning library to do hyper parameter tuning for their deep learning models. >>They can also use it for inference and you know, because these are all built on top of Ray, they inherit the like, elasticity and fault tolerance of running on top of Ray. So really it simplifies things on the infrastructure side cuz there's just, if you have Ray as common infrastructure for your machine learning workloads, there's just one system to, to kind of manage and operate. And if you are, it simplifies things for the end users like the developers because from their perspective, they're just writing a Python application. They don't have to learn how to use three different distributed systems and stitch them together and all of this. >>So aws, before I let you go, how do they come into play here for you? I mean, are you part of the showcase, a startup showcase? So obviously a major partner and major figure in the offering that you're presenting >>People? Yeah, well you can run. So any scale is a managed ray service. Like any scale is just the best way to run Ray and deploy Ray. And we run on top of aws. So many of our customers are, you know, using Ray through any scale on aws. And so we work very closely together and, and you know, we have, we have joint customers and basically, and you know, a lot of the value that any scale is adding on top of Ray is around the production story. So basically, you know, things like high availability, things like failure handling, retry alerting, persistence, reproducibility, these are a lot of the value, the values of, you know, the value that our platform adds on top of the open source project. A lot of stuff as well around collaboration, you know, imagine you are, you, something goes wrong with your application, your production job, you want to debug it, you can just share the URL with your, your coworker. They can click a button, reproduce the exact same thing, look at the same logs, you know, and, and, and figure out what's going on. And also a lot around, one thing that's, that's important for a lot of our customers is efficiency around cost. And so we >>Support every customer. >>Exactly. A lot of people are spending a lot of money on, on aws. Yeah. Right? And so any scale supports running out of the box on cheaper like spot instances, these preempt instances, which, you know, just reduce costs by quite a bit. And so things like that. >>Well, the company is any scale and you're on the show floor, right? So if you're having a chance to watch this during reinvent, go down and check 'em out. Robert Ashihara joining us here, the co-founder and ceo and Robert, thanks for being with us. Yeah. Here on the cube. Really enjoyed it. Me too. Thanks so much. Boy, three years graduate program and boom, here you are, you know, with off to the enterprise you go. Very nicely done. All right, we're gonna continue our coverage here on the Cube with more here from Las Vegas. We're the Venetian, we're AWS Reinvent 22 and you're watching the Cube, the leader in high tech coverage.

>>Good afternoon everybody. I'm John Walls and welcome back to our coverage here on the cube of AWS Reinvent 22. We are bringing you another segment with the Global Startup Program, which is part of the AWS Start Showcase, and it's a pleasure to welcome two new guests here to the showcase. First, immediately to my right Han w lre. Good to see you Han. Good to see you. The leader of the Enterprise Solutions Architecture at aws. And on the far right, Rolin Lee, who is the co-founder and CEO of Heim Doll Data. Roland, good to see you. Great >>To be here. >>All right, good. Thanks for joining us. Well first off, for those at home, I may not be familiar with Heim Doll. What do you do? Why are you here? But I'll let you take it from there. >>Well, we're one of the sponsors here at AWS and great to be here. We offer a data access layer in the form of a proxy, and what it does is it provides complete visibility and the capability to enhance the interaction between the application and one's current database. And as a result, you'll, the customer will improve database scale, database security and availability. And all these features don't require any application changes. So that's sort of our marketing pitch, if you will, all these types of features to improve the experience of managing a database without any application >>Changes. And, and where's the cloud come into play then, for you then, where, where did it come into play for you? >>So we started out actually helping out customers on premise, and a lot of enterprise customers are moving over to the cloud, and it was just a natural progression to do that. And so aws, which is a key part of ours, partners with us to help solve customer problems, especially on the database side, as the application being application performance tends to have issues between the interaction between the application database and we're solving that issue. >>Right. Sohan, I mean, Roan just touched on it about OnPrem, right? There's still some kickers and screamers out there that, that don't, haven't bought in or, or they're about to, but you're about to get 'em. I, I'm sure. But talk about that, that conversion or that transition, if you would, from going OnPrem into a hybrid environment or to into the, the bigger cloud environment and and how difficult that is sometimes. Yes. Maybe to get people to, to make that kind of a leap. >>Well, I would say that a lot of customers are wanting to focus more on product innovation experimentation, and also in terms of having to manage servers and patching, you know, it's to take away from that initiative that they're trying to do. So with aws, we provide undifferentiated heavy lifting so that they can focus on product innovation. And one of the areas talking about Heim is that from the database side, we do provide Amazon rds, which is database and also Aurora, to give them that lift so they don't have to worry about patching servers and setting up provisioning servers as well. >>Right. So Roland, can you get the idea across to people very simply, let us take care of the, the hard stuff and, and that will free you up to do your product innovations, to do your experimentations to, to really free up your team, basically to do the fun stuff and, and let us sweat over the, the, the details basically. Right? >>Exactly. Our, our motto is not only why build when, when you can buy. So a lot of it has to do with offering the, the value in terms of price and the features such as it's gonna benefit a team. Large companies like amazon.com, Google, they have huge teams that can build data access layers and proxies. And what we're trying to do here is commercialize those cuz those are built in house and it's not readily available for customers to use. And you'd need some type of interface between the application and the database. And we provide that sort of why build when you can buy. >>Well, I was gonna say why h right? I mean what's your special sauce? Because everybody's got something, obviously a market differentiator that you're bringing into place here. So you started to touch on a little bit there for me, but, but dive a little deeper there. I mean, what, what is it that, that you're bringing to the table with AWS that you think puts you above the crowd? >>Well, lemme give you a use case here. In typical events like let's say Black Friday where there's a surge traffic that can overwhelm the database, the Heim doll data access layer database proxy provides an auto scaling distributed architecture such that it can absorb those surges and traffic and help scale the database while keeping the data fresh and up to date. And so basically traffic based on season time of day, we can, we can adjust automatically and all these types of features that we offer, most notably automated query caching, ReadWrite split for asset compliance don't require any code changes, which typically requires the application developer to make those changes. So we're saving months, maybe years of development and maintenance. >>Yeah, a lot of gray hairs too, right? Yeah, you're, you're solving a lot of problems there. What about database trends in just in general Hunt, if you will. I mean, this is your space, right? I mean, what we're hearing about from Heindel, you know, in terms of solutions they're providing, but what are you seeing just from the macro level in terms of what people are doing and thinking about the database and how it relates to the cloud? Right. >>And some of the things that we're seeing is that we're seeing an explosion of data, relevant data that customers need to be able to consume and also process as well. So with the explosion of data, there's also, we see customers trying to modernize their application as well through microservices, which does change the design patterns of like the applications we call the access data patterns as well. So again, going back to that, a differentiated heavy lifting, we do have something called purpose built databases, right? It's the right tool for the right purpose. And so it depends on what their like rpo, rto their access to data pattern. Is it a base, is it an acid? So we want to be able to provide them the options to build and also innovate. So with that, that's why we have the Amazon rds, the also the, we also have Redshift, we also have Aurora and et cetera. The Rediff is more of the BI side, but usually when you ingest the data, you have some level of processing to get more insight. So with that, that's why customers are moving more of towards the managed service so that they can give that lift and then focusing on that product and innovation. Yeah. >>Have we kind of caught up or are we catching up to this just the tsunami of data to begin with, right? Because I mean, that was it, you know, what, seven, eight years ago when, when that data became kind of, or becoming king and, and reams and reams and reams and all, you know, can't handle it, right? And, and are we now able to manage that process and manage that flow and get the right data into the right hands at the right time? We're doing better with that. >>I would say that it, it definitely has grown in size of the amount of data that we're ingesting. And so with the scalability and agility of the cloud, we're able to, I would say, adapt to the rapid changes and ingestions of the data. So, so that's why we have things like Aurora servers to have that or auto scale so they can do like MySQL or Postgres and then they can still, like what you know, I'm trying to do is basically don't have to co do like any code changes. It would be a data migration. They still use the same underlying database on also mechanisms, but here we're providing them at scale on the cloud. >>Yeah. Our proxies, they must have for all databases. I mean, is that, is that essential these days? >>Well, good question John. I would say yes. And this is often built in house, as I mentioned, for large companies, they do build some type of data access layer or proxy and, or some utilize some orm, some object relational map to do it. And what again, what we're trying to do is offer this, put this out into the market commercially speaking, such that it can be readily used for, for all the customers to use rather than building it from scratch all the time. >>You know what I didn't ask you was Roy, how does AWS come into play for you then? And, and as in the startup mode, the focus that they've had in startups in general, but in you in particular, I mean, talk about that partnership or that relationship and the value that you're extracting from that. >>The ad AWS partnership has been absolutely wonderful. The collaboration, they have one of the best managed service databases. The value that it that adds in terms of the durability, the manageability, what the Heim doll data does is it compliments Amazon rds, Amazon Redshift very well in the sense that we're not replacing the database. What we're doing is we are allowing the customer to get the most out of the managed service database, whether it be Redshift or Aurora Serverless, rds, all without code changes. And or the analogy that I would give John is a car, a race car may be very fast, but it takes a driver to get to those fast speeds. We're the driver, the Hyundai proxy provides that intelligence so that you can get the most out of that database engine. >>And, and Hfi would then touch on, first off AWS and the emphasis that you have put on startups and are obviously, you know, kind of putting your money where your mouth is, right? With, with the way you've encouraged and nurtured that environment. And they would be about Heim doll in general about where you see this going or what you would like to have, where you want to take this in the next say 12 months, 18 months. >>I think it's more of a better together story of how we can basically coil with our partners, right? And, and basically focusing on helping our customers drive that innovation and be collaboration. So as Heim, as a independent service vendor isv, most customers can leverage that through a marketplace where basically it integrates very nicely with aws. So that gives 'em that lift and it goes back to the undifferentiated heavy lifting on the Hein proxy side, if you will, because then you have this proxy in the middle where then it helps them with their SQL performance. And I've seen use cases where customers were, have some legacy system that they may not have time to modernize the application. So they use this as a lift to keep, keep going as they try to modernize. But also I've seen customers who use are trying to use it as a, a way to give that performance lift because they may have a third party software that they cannot change the code by putting this in there that helps optimize their lines of business or whatever that is, and maybe can be online store or whatever. So I would say it was a better together type of story. >>Yeah. Which is, there's gotta be a song in there somewhere. So peek around the corner and if you wanna be headlights here right now in terms of 12, 18 months, I mean, what, you know, what what next to solve, right? You've already taken, you've slayed a few dragons along the way, but there are others I'm sure is it always happens in innovation in this space. Just when you solve a problem you've just dealt or you have to deal with others that pop up as maybe unintended consequences or at least a new challenge. So what would that be in your world right now? What, what do you see, you know, occupying your sleepless nights here for the next year or so? >>Well, for, for HOMEDALE data, it's all about improving database performance and scale. And those workloads change. We have O ltp, we have OLA with artificial intelligence ml. There's different type of traffic profiles and we're focused on improving those data profiles. It could be unstructured structured. Right now we're focused on structured data, which is relational databases, but there's a lot of opportunity to improve the performance of data. >>Well, you're driving the car, you got a good navigator. I think the GPS is working. So keep up the good work and thank you for sharing the time today. Thank you. Thank you, joy. Do appreciate it. All right, you are watching the cube. We continue our coverage here from AWS Reinvent 22, the Cube, of course, the leader in high tech coverage.

>> Well, welcome back here to the Venetian. We're in Las Vegas. It is Wednesday, Day 2 of our coverage here of AWS re:Invent, 22. I'm your host, John Walls on theCUBE and it's a pleasure to welcome in two more guests as part of our AWS startup showcase, which is again part of the startup program globally at AWS. I've got Anant Verma, who is the Vice President of Engineering at Elation. Anant, good to see you, sir. >> Good to see you too. >> Good to be with us. And Haseeb Budhani, who is the CEO and co-founder of Rafay Systems. Good to see you, sir. >> Good to see you again. >> Thanks for having, yeah. A cuber, right? You've been on theCUBE? >> Once or twice. >> Many occasions. But a first timer here, as a matter of fact, glad to have you aboard. All right, tell us about Elation. First for those whom who might not be familiar with what you're up to these days, just give it a little 30,000 foot level. >> Sure, sure. So, yeah, Elation is a startup and a leader in the enterprise data intelligence space. That really includes a lot of different things including data search, data discovery, metadata management, data cataloging, data governance, data policy management, a lot of different things that companies want to do with the hoards of data that they have and Elation, our product is the answer to solve some of those problems. We've been doing pretty good. Elation is in running for about 10 years now. We are a series A startup now, we just raised around a few, a couple of months ago. We are already a hundred million plus in revenue. So. >> John: Not shabby. >> Yeah, it's a big benchmark for companies to, startup companies, to cross that milestone. So, yeah. >> And what's the relationship? I know Rafay and you have worked together, in fact, the two of you have, which I find interesting, you have a chance, you've been meeting on Zoom for a number of months, as many of us have it meeting here for the first time. But talk about that relationship with Rafay. >> Yeah, so I actually joined Elation in January and this is part of the move of Elation to a more cloud native solution. So, we have been running on AWS since last year and as part of making our solution more cloud native, we have been looking to containerize our services and run them on Kubernetes. So, that's the reason why I joined Elation in the first place to kind of make sure that this migration or move to a cloud native actually works out really well for us. This is a big move for the companies. A lot of companies that have done in the past, including, you know, Confluent or MongoDB, when they did that, they actually really reap great benefits out of that. So to do that, of course, you know, as we were looking at Kubernetes as a solution, I was personally more looking for a way to speed up things and get things out in production as fast as possible. And that's where I think, Janeb introduced us... >> That's right. >> Two of us. I think we share the same investor actually, so that's how we found each other. And yeah, it was a pretty simple decision in terms of, you know, getting the solution, figuring it out if it's useful for us and then of course, putting it out there. >> So you've hit the keyword, Kubernetes, right? And, so if you would to honestly jump in here, there are challenges, right? That you're trying to help them solve and you're working on the Kubernetes platform. So, you know, just talk about that and how that's influenced the work that the two of you are doing together. >> Absolutely. So, the business we're in is to help companies who adopt Kubernetes as an orchestration platform do it easier, faster. It's a simple story, right? Everybody is using Kubernetes, but it turns out that Kubernetes is actually not that easy to to operationalize, playing in a sandbox is one thing. Operationalizing this at a certain level of scale is not easy. Now, we have a lot of enterprise customers who are deploying their own applications on Kubernetes, and we've had many, many of them. But when it comes to a company like Elation, it's a more complicated problem set because they're taking a very complex application, their application, but then they're providing that as a service to their customers. So then we have a chain of customers we have to make happy. Anant's team, the platform organization, his internal customers who are the developers who are deploying applications, and then, the company has customers, we have to make sure that they get a good experience as they consume this application that happens to be running on Kubernetes. So that presented a really interesting challenge, right? How do we make this partnership successful? So I will say that, we've learned a lot from each other, right? And, end of the day, the goal is, my customer, Anant's specifically, right? He has to feel that, this investment, 'cause he has to pay us money, we would like to get paid. >> John: Sure. (John laughs) >> It reduces his internal expenditure because otherwise he'd have to do it himself. And most importantly, it's not the money part, it's that he can get to a certain goalpost significantly faster because the invention time for Kubernetes management, the platform that you have to build to run Kubernetes is a very complex exercise. It took us four and a half years to get here. You want to do that again, as a company, right? Why? Why do you want to do that? We, as Rafay, the way I think about what we deliver, yes, we sell a product, but to what end? The product is the what, the why, is that every enterprise, every ISV is building a Kubernetes platform in house. They shouldn't, they shouldn't need to. They should be able to consume that as a service. They consume the Kubernetes engine the EKS is Amazon's Kubernetes, they consume that as an engine. But the management layer was a gap in the market. How do I operationalize Kubernetes? And what we are doing is we're going to, you know, the Anant said. So the warden saying, "Hey you, your team is technical, you understand the problem set. Would you like to build it or would you rather consume this as a service so you can go faster?" And, resoundingly the answer is, I don't want to do this anymore. I wouldn't allow to buy. >> Well, you know, as Haseeb is saying, speed is again, when we started talking, it only took us like a couple of months to figure out if Rafay is the right solution for us. And so we ended up purchasing Rafay in April. We launched our product based on Rafay in Kubernetes, in EKS in August. >> August. >> So that's about four months. I've done some things like this before. It takes a couple of years just to sort of figure out, how do you really work with Kubernetes, right? In a production at a large scale. Right now, we are running about a 600 node cluster on Rafay and that's serving our customers. Like, one of the biggest thing that's actually happening on December 8th is we are running what we call a virtual hands on lab. >> A virtual? >> Hands on lab. >> Okay. >> For Elation. And they're probably going to be about 500 people is going to be attending it. It's like a webinar style. But what we do in that hands on lab is we will spin up an Elation instance for each attendee, right on the spot. Okay? Now, think about this enterprise software running and people just sign up for it and it's there for you, right on the spot. And that's the beauty of the software that we have been building. There's the beauty of the work that Rafay has helped us to do over the last few months. >> Okay. >> I think we need to charge them more money, I'm getting from this congregation. I'm going to go work on that. >> I'm going to let the two of you work that out later. All right. I don't want to get in the way of a big deal. But you mentioned that, we heard about it earlier that, it's you that would offer to your cert, to your clients, these services. I assume they have their different levels of tolerance and their different challenges, right? They've got their own complexities and their own organizational barriers. So how are you juggling that end of it? Because you're kind of learning as, well, not learning, but you're experiencing some of the thing. >> Right. Same things. And yet you've got this other client base that has a multitude of experiences that they're going through. >> Right. So I think, you know a lot of our customers, they are large enterprise companies. They got a whole bunch of data that they want work with us. So one of the thing that we have learned over the past few years is that we used to actually ship our software to the customers and then they would manage it for their privacy security reasons. But now, since we're running in the cloud, they're really happy about that because they don't need to juggle with the infrastructure and the software management and upgrades and things like that, we do it for them, right? And, that's the speed for them because now they are only interested in solving the problems with the data that they're working with. They don't need to deal with all these software management issues, right? So that frees our customers up to do the thing that they want to do. Of course it makes our job harder and I'm sure in turn it makes his job harder. >> We get a short end of the stick, for sure. >> That's why he is going to get more money. >> Exactly. >> Yeah, this is a great conversation. >> No, no, no. We'll talk about that. >> So, let's talk about the cloud then. How, in terms of being the platform where all this is happening and AWS, about your relationship with them as part of the startup program and what kind of value that brings to you, what does that do for you when you go out and are looking for work and what kind of cache that brings to you >> Talk about the AWS? >> Yes, sir. >> Okay. Well, so, the thing is really like of course AWS, a lot of programs in terms of making sure that as we move our customers into AWS, they can give us some, I wouldn't call it discount, but there's some credits that you can get as you move your workloads onto AWS. So that's a really great program. Our customers love it. They want us to do more things with AWS. It's a pretty seamless way for us to, as we were talking about or thinking about moving into the cloud, AWS was our number one choice and that's the only cloud that we are in, today. We're not going to go to any other place. >> That's it. >> Yeah. >> How would you characterize? I mean, we've already heard, from one side of the fence here, but. >> Absolutely. So for us, AWS is a make or break partner, frankly. As the EKS team knows very well, we support Azure's Kubernetes and Google's Kubernetes and the community Kubernetes as well. But the number of customers on our platform who are AWS native, either a hundred percent or a large percentage is, you know, that's the majority of our customer base. >> John: Yeah. >> And AWS has made it very easy for us in a variety of ways to make us successful and our customers successful. So Anant mentioned the credit program they have which is very useful 'cause we can, you know, readily kind of bring a customer to try things out and they can do that at no cost, right? So they can spin up infrastructure, play with things and AWS will cover the cost, as one example. So that's a really good thing. Beyond that, there are multiple programs at AWS, ISV accelerate, et cetera. That, you know, you got to over time, you kind of keep getting taller and taller. And you keep getting on bigger and bigger. And as you make progress, what I'm finding is that there's a great ecosystem of support that they provide us. They introduce us to customers, they help us, you know, think through architecture issues. We get access to their roadmap. We work very, very closely with the guest team, for example. Like the, the GM for Kubernetes at AWS is a gentleman named Barry Cooks who was my sponsor, right? So, we spend a lot of time together. In fact, right after this, I'm going to be spending time with him because look, they take us seriously as a partner. They spend time with us because end of the day, they understand that if they make their partners, in this case, Rafay successful, at the end of the day helps the customer, right? Anant's customer, my customer, their AWS customers, also. So they benefit because we are collectively helping them solve a problem faster. The goal of the cloud is to help people modernize, right? Reduce operational costs because data centers are expensive, right? But then if these complex solutions this is an enterprise product, Kubernetes, at the enterprise level is a complex problem. If we don't collectively work together to save the customer effort, essentially, right? Reduce their TCO for whatever it is they're doing, right? Then the cost of the cloud is too high. And AWS clearly understands and appreciates that and that's why they are going out of their air, frankly, to make us successful and make other companies successful in the startup program. >> Well. >> I would just add a couple of things there. Yeah, so, you know, cloud is not new. It's been there for a while. You know, people used to build things on their own. And so what AWS has really done is they have advanced technology enough where everything is really simple as just turning on a switch and using it, right? So, just a recent example, and I, by the way, I love managed services, right? So the reason is really because I don't need to put my own people to build and manage those things, right? So, if you want to use a search, they got the open search, if you want to use caching, they got elastic caching and stuff like that. So it's really simple and easy to just pick and choose which services you want to use and they're ready to be consumed right away. And that's the beautiful, and that that's how we can move really fast and get things done. >> Ease of use, right? Efficiency, saving money. It's a winning combination. Thanks for sharing this story, appreciate. Anant, Haseeb thanks for being with us. >> Yeah, thank you so much having us. >> We appreciate it. >> Thank you so much. >> You have been a part of the global startup program at AWS and startup showcase. Proud to feature this great collaboration. I'm John Walls. You're watching theCUBE, which is of course the leader in high tech coverage.

>>And welcome back to the Cube everyone. I'm John Walls to continue our coverage here of AWS Reinvent 22. We're part of the AWS Startup Showcase is the global startup program that AWS so proudly sponsors and with us to talk about what they're doing now in the AWS space. Shaun Knapps, the CEO of AS Send IO and Sean, good to have here with us. We appreciate >>It. Thanks for having me, >>John. Yeah, thanks for the time. First off, gotta show the t-shirt. You caught my attention. Big data is a cluster. I don't think you get a lot of argument from some folks, right? But it's your job to make some sense of it, is it not? Yeah. Tell us about a Send io. >>Sure. As Send IO is a data automation platform. What we do is connect a lot of the, the disparate parts of what data teams do when they create ETL and E o T data pipelines. And we use advanced levels of automation to make it easier and faster for them to build these complex systems and have their world be a little bit less of a, a cluster. >>All right. So let's get into automation a little bit then again, I, your definition of automation and how you're applying it to your business case. >>Absolutely. You know, what we see oftentimes is as spaces mature and evolve, the number of repetitive and repeatable tasks that actually become far less differentiating, but far more taxable if you will, right to the business, start to accumulate as those common patterns emerge. And, and, you know, as we see standardization around tech stacks, like on Amazon and on Snowflake and on data bricks, and as you see those patterns really start to, to formalize and standardize, it opens up the door to basically not have your team have to do all those things anymore and write code or perform the same actions that they used to always have to, and you can lean more on technology to properly automate and remove the, the monotony of those tasks and give your teams greater leverage. >>All right. So, so let's talk about at least maybe your, the journey, say in the past 18 months in terms of automation and, and what have you seen from a trend perspective and how are you trying to address that in order to, to meet that need? >>Yeah, I think the last 18 months have become, you know, really exciting as we've seen both that, you know, a very exciting boom and bust cycle that are driving a lot of other macro behaviors. You know, what we've seen over the last 18 months is far greater adoption of the, the standard, what we call the data planes, the, the architectures around snowflake and data bricks and, and Amazon. And what that's created as a result is the emergence of what I would call is the next problem. You know, as you start to solve that category of how >>You, that's it always works too, isn't >>It? Yeah, exactly. Always >>Works that >>This is the wonderful thing about technology is the job security. There's always the next problem to go solve. And that's what we see is, you know, as we we go into cloud, we get that infinite scale, infinite capacity, capacity, infinite flexibility. And you know, with these modern now data platforms, we get that infinite ability to store and process data incredibly quickly with incredible ease. And so what, what do most organizations do? You take a ton of new bodies, like all the people who wanted to do those like really cool things with data you're like, okay, now you can. And so you start throwing a lot more use cases, you start creating a lot more data products, you start doing a lot more things with data. And this is really where that third category starts to emerge, which is you get this data mess, not mesh, but the data mess. >>You get a cluster cluster, you get a cluster exactly where the complexity skyrockets. And as a result that that rapid innovation that, that you are all looking for and, and promised just comes to a screeching halt as you're just, just like trying to swim through molasses. And as a result, this is where that, that new awareness around automation starts really heightened. You know, we, we did a really interesting survey at the start of this year, did it as a blind survey, independent third party surveyed, 500 chief data officers, data scientists, data architects, and asked them a plethora of questions. But one of the questions we asked them was, do you currently or do you intend on investing in data automation to increase your team's productivity? And what was shocking, and I was very surprised by this, okay, what was shocking was only three and a half percent said they do today. Which is really interesting because it really hones in on this notion of automation is beyond what a lot of a think of, you know, tooling and enhancements today, only three and a half percent today had it, but 88.5% said they intend on making data automation investments in the next 12 months. And that stark contrast of how many people have a thing and how many people want that benefit of automation, right? I think it is incredibly critical as we look to 2023 and beyond. >>I mean, this seems like a no-brainer, does it not? I mean, know it is your business, of course you agree with me, but, but of course, of course what brilliant statement. But it is, it seems like, you know, the more you're, you're able to automate certain processes and then free up your resources and your dollars to be spent elsewhere and your, and your human capital, you know, to be invested elsewhere. That just seems to be a layup. I'm really, I'm very surprised by that three and a half percent figure >>I was too. I actually was expecting it to be higher. I was expecting five to 10%. Yeah. As there's other tools in the, the marketplace around ETL tools or orchestration tools that, that some would argue fit in the automation category. And I think the, what, what the market is telling us based on, on that research is that those themselves are, don't qualify as automation. That, that the market has a, a larger vision for automation. Something that is more metadata driven, more AI back, that takes us a greater leap and of leverage for the teams than than what the, the existing capabilities in the industry today can >>Afford. Okay. So if you got this big leap that you can make, but, but, but maybe, you know, should sites be set a little lower, are you, are you in danger of creating too much of an expectation or too much of a false hope? Because you know, I mean sometimes incremental increases are okay. I >>Agree. I I I think the, you know, I think you wanna do a little bit of both. I think you, you want to have a plan for, for reaching for the stars and you gotta be really pragmatic as well. Even inside of a a suni, we actually have a core value, which is build for 10 x plan for a hundred x and so know where you're going, right? But, but solve the problems that are right in front of you today as, as you get to that next scale. And I think the, the really important part for a lot of companies is how do you think about what that trajectory is and be really smart around where you choose to invest as you, one of the, the scenes that we have is last year's innovation is next year's anchor around your neck. And that's because we, we were in this very fortunately, so this really exciting, rapidly moving innovative space, but the thing that was your advantage not too long ago is everybody can move so quickly now becomes commonplace and a year or two later, if you don't jump on whatever that next innovation is that the industry start to standardize on, you're now on hook paying massive debt and, and paying, you know, you thought you had, you know, home mortgage debt and now you're paying the worst of credit card debt trying to pay that down and maintain your velocity. >>It's >>A whole different kind of fomo, right? I'm fair, miss, I'm gonna miss out. What am I missing out on? What the next big thing exactly been missing out >>On that? And so we encourage a lot of folks, you know, as you think about this as it pertains to automation too, is you solve for some of the problems right in front of you, but really make sure that you're, you're designing the right approach that as you stack on, you know, five times, 10 times as many people building data products and, and you, you're, you're your volume and library of, of data weaving throughout your, your business, make sure you're making those right investments. And that's one of the reasons why we do think automation is so important and, and really this, this next generation of automation, which is a, a metadata and AI back to level of automation that can just achieve and accomplish so much more than, than sort of traditional norms. >>Yeah. On that, like, as far as Dex Gen goes, what do you think is gonna be possible that cloud sets the stage for that maybe, you know, not too long ago seem really outta reach, like, like what's gonna give somebody to work on that 88% in there that's gonna make their spin come your way? >>Ah, good question. So I, I think there's a couple fold. I, you know, I think the, right now we see two things happening. You know, we see large movements going to the, the, the dominant data platforms today. And, and you know, frankly, one of the, the biggest challenges we see people having today is just how do you get data in which is insanity to me because that's not even the value extraction, that is the cost center piece of it. Just get data in so you can start to do something with it. And so I think that becomes a, a huge hurdle, but the access to new technologies, the ability to start to unify more of your data and, and in rapid fashion, I think is, is really important. I think as we start to, to invest more in this metadata backed layer that can connect that those notions of how do you ingest your data, how do you transform it, how do you orchestrate it, how do you observe it? One of the really compelling parts of this is metadata does become the new big data itself. And so to do these really advanced things to give these data teams greater levels of automation and leverage, we actually need cloud capabilities to process large volumes of not the data, but the metadata around the data itself to deliver on these really powerful capabilities. And so I think that's why the, this new world that we see of the, the developer platforms for modern data cloud applications actually benefit from being a cloud native application themselves. >>So before you take off, talk about the AWS relationship part of the startup showcase part of the growth program. And we've talked a lot about the cloud, what it's doing for your business, but let's just talk about again, how integral they have been to your success and, and likewise what you're thinking maybe you bring to their table too. Yeah, >>Well we bring a lot to the table. >>Absolutely. I had no doubt about that. >>I mean, honestly, it, working with with AWS has been truly fantastic. Yep. You know, I think, you know, as a, a startup that's really growing and expanding your footprint, having access to the resources in AWS to drive adoption, drive best practices, drive awareness is incredibly impactful. I think, you know, conversely too, the, the value that Ascend provides to the, the AWS ecosystem is tremendous leverage on onboarding and driving faster use cases, faster adoption of all the really great cool, exciting technologies that we get to hear about by bringing more advanced layers of automation to the existing product stack, we can make it easier for more people to build more powerful things faster and safely. Which I think is what most businesses at reinvent really are looking for. >>It's win-win, win-win. Yeah. That's for sure. Sean, thanks for the time. Thank you John. Good job on the t-shirt and keep up the good work. Thank you very much. I appreciate that. Sean Na, joining us here on the AWS startup program, part of their of the Startup Showcase. We are of course on the Cube, I'm John Walls. We're at the Venetian in Las Vegas, and the cube, as you well know, is the leader in high tech coverage.

>>And good afternoon. Welcome back here on the Cub as to continue our coverage at aws Reinvent 22, win the Venetian here in Las Vegas, day two, it's Wednesday. Thanks. Still rolling. Quite a along. We have another segment for you as part of the Global Startup program, which is under the AWS Startup Showcase. I'm joined now by Vink at Viera, who is the CEO and co-founder of R Set. And good to see you, >>Sir. Thanks for having me here. Yeah, >>No, a real pleasure. Looking forward to it. So first off, for some of, for yours who might not be familiar with Roxette, I know you've been on the cube a little bit, so you're, you're an alum, but, but why don't you set the stage a little bit for Rock set and you know, where you're engaged with in terms of, with aws? >>Definitely. Rock Set is a realtime analytics database that is built for the cloud. You know, we make realtime applications possible in the cloud. You know, realtime applications need high concurrency, low latency query processing data needs to be fresh, your analytic needs to be fast. And, you know, we built on aws and that's why we are here. We are very, very proud partners of aws. We are in the AWS Accelerate program, and also we are in the startup program of aws. We are strategic ISV partner. And so yeah, we make real time analytics possible without all the cost and complexity barriers that are usually associated with it. And very, very happy to be part of this movement from batch to real time that is happening in the world. >>Right. Which is certainly an exciting trend. Right. I know great news for you, you made news yesterday, had an announcement involved with the intel with aws, who wants to share some of that >>With us too? Definitely. So, you know, one, one question that I always ask people is like, you know, if you go perspective that I share is like, if you go ask a hundred people, do you want fast analytics on fresh data or slow analytics on stale data? You know, a hundred out of a hundred would say fast and fresh, right? Sure. So then the question is, why hasn't this happened already? Why is this still a new trend that is emerging as opposed to something that everybody's taking for granted? It really comes down to compute efficiency, right? I think, you know, at the end of the day, real time analytics was always in using, you know, technologies that are, let's say 10 years ago using let's say processors that were available 10 years ago to, you know, three cloud, you know, days. There was a lot of complexity barriers associated with realtime analytics and also a lot of cost and, and performance barriers associated with it. >>And so Rox said from the, you know, from the very beginning, has been obsessing about building the most compute efficient realtime database in the world. And, you know, AWS on one hand, you know, allows us to make a consumption based pricing model. So you only pay for what you use. Sure. And that shatters all the cost barriers. But in terms of computer efficiency, what we announced yesterday is the Intel's third generation Zon scalable processors, it's code named Intel Ice Lake. When we port it over Rock said to that architecture, taking advantage of some of the instructions sets that Intel has, we got an 84% performance boost, 84, 84, 84. >>It's, it's incredible, right? >>It's, it's an incredible charts, it's an incredible milestone. It reduces the barrier even more in terms of cost and, you know, and, and pushes the efficiency and sets a, a really new record for how efficient realtime, you know, data processing can be in the cloud. And, and it's very, very exciting news. And so we used to benchmark ourselves against some of our other, you know, realtime, you know, did up providers and we were already faster and now we've set a, a much, much higher bar for other people to follow. >>Yep. And, and so what is, or what was it about real time that, that, you know, was such a barrier because, and now you've got the speed of, of course, obviously, and maybe that's what it was, but I think cost is probably part of that too, right? That's all part of that equation. I mean, real time, so elusive. >>Yeah. So real time has this inherent pattern that your data never stops coming. And when your data never stops coming, and you can now actually do analytics on that. Now, initially people start with saying, oh, I just want a real time dashboard. And then very quickly they realize, well, the dashboard is actually in real time. I'm not gonna be staring at the 24 7. Can you tap on my shoulder when something is off, something needs to be looked at. So in which case you're constantly also asking the question, is everything okay? Is everything all right? Do I need to, is is that something that I need to be, you know, double clicking on and, and following up on? So essentially very quickly in real time analytics, what happens is your queries never stop. The questions that you're asking on your data never stops. And it's often a program asking the question to detect anomalies and things like that. >>And your data never stops coming. And so compute is running 24 7. If you look at traditional data warehouses and data lakes, they're not really optimized for these kinds of workloads. They're optimized to store massive volumes of data and in a storage efficient format. And when an analyst comes and asks a question to generate a report, you can spin up a whole bunch of compute, generate the report and tear it all down when you're done. Well, that is not compute running 24 7 to continuously, you know, you know, keep ingesting the data or continuously keep answering questions. So the compute efficiency that is needed is, is much, much, much higher. Right? And that is why, you know, Rox was born. So from the very beginning, we're only built, you know, for these use cases, we have a, an extremely powerful SQL engine that can give you full feature SQL analytics in a very, very compute efficient way in the cloud. >>Right. So, so let's talk about the leap that you've made, say in the last two years and, and, and what's been the spur of that? What has been allowed you to, to create this, you know, obviously a, a different kind of an array for your customers from which to choose, but, but what's been the spark you think >>We touched upon this a little earlier, right? This spark is really, you know, the world going from batch to real time. So if you look at mainstream adoption of technologies like Apache, Kafka and Confluent doing a really good job at that. In, in, in growing that community and, and use cases, now businesses are now acquiring business data, really important business data in real time. Now they want to operationalize it, right? So, you know, extract based static reports and bi you know, business intelligence is getting replaced in all modern enterprises with what we call operational intelligence, right? Don't tell me what happened last quarter and how to plan this quarter better. Tell me what's happening today, what's happening right now. And it's, it's your business operations using data to make day to day decisions better that either grows your top line, compresses your bottom line, eliminates risk that are inherently creeping up in your business. >>Sure. You know, eliminate potential churn from a customer or fraud, you know, deduction and, and getting on top of, you know, that, you know, a minute into this, into, into an outage as opposed to an hour into the outage. Right? And so essentially I think businesses are now realizing that operational intelligence and operational analytics really, you know, allows them to leverage data and especially real time data to make their, you know, to grow their businesses faster and more efficiently. And especially in this kind of macro environment that is, you know, more important to have better unit economics in your business than ever before. Sure. And so that is really, I think that is the real market movement happening. And, and we are here to just serve that market. We are making it much, much easier for companies that have already adopted, you know, streaming technologies like Kafka and, and, and knows Canis MSK and all these technologies. Now businesses are acquiring these data in real time now. They can also get realtime analytics on the other end of it. Sure. >>You know, you just touched on this and, and I'd like to hear your thoughts about this, about, about the economic environment because it does drive decisions, right? And it does motivate people to look for efficiencies and maybe costs, you know, right. Cutting costs. What are you seeing right now in terms of that, that kind of looming influence, right? That the economy can have in terms of driving decisions about where investments are being made and what expectations are in terms of delivering value, more value for the buck? >>Exactly. I think we see across the board, all of our customers come back and tell us, we don't want to manage data infrastructure and we don't want to do kind of DIY open source clusters. We don't wanna manage and scale and build giant data ops and DevOps teams to manage that, because that is not really, you know, in their business. You know, we have car rental companies want to be better at car rentals, we want airlines to be a better airline, and they don't, don't want their, you know, a massive investment in DevOps and data ops, which is not really their core business. And they really want to leverage, you know, you know, fully managed and, you know, cloud offerings like Rock said, you know, built on aws, massively scalable in the cloud with zero operational overhead, very, very easy to get started and scale. >>And so that completely removes all the operational overhead. And so they can invest the resources they have, the manpower, they have, the calories that they have on actually growing their businesses because that is what really gonna allow them to have better unit economics, right? So everybody that is on my payroll is helping me grow my top line or shrink my bottom line, eliminate risk in my business and, and, and, and churn and, and fraud and other, and eliminate all those risks that are inherent in my business. So, so that is where I think a lot of the investments going. So gone are the days where, you know, you're gonna have these in like five to 10% team managing a very hard to operate, you know, open source data management clusters on EC two nodes in, in AWS and, and kind of DIYing it their way because those 10 people, you know, if all they do is just operational maintenance of infrastructure, which is a means to an end, you're way better off, you know, using a cloud, you know, a bond in the cloud built for the cloud solution like rock and eliminate all that cost and, and replace that with an operationally much, much simpler, you know, system to op, you know, to to work with such as, such as rock. >>So that is really the big trend that we are seeing why, you know, not only real time is going more and more mainstream cloud native solutions or the real future even when it comes to real time because the complexity barrier needs to be shattered and only cloud native solutions can actually, >>You get the two Cs cost and complexity, right. That you, you need to address. Exactly. Yeah, for sure. You know, what is it about building trust with your, with your clients, with your partners? Because you, you're talking about this cloud environment that, that everyone is talking about, right? Not everyone's made that commitment. There are still some foot draggers out there. How are you going about establishing confidence and establishing trust and, and, and providing them with really concrete examples of the values and the benefits that you can provide, you know, with, with these opportunities? >>So, you know, I grew up, so there's a few ways to to, to answer this question. I'll, I'll, I'll come, I'll cover all the angles. So in, in order to establish trust, you have to create value. They, you know, your customer has to see that with you. They were able to solve the problem faster, better, cheaper, and they're able to, you know, have a, the business impact they were looking for, which is why they started the project in the first place. And so establishing that and proving that, I think there's no equivalence to that. And, you know, I grew up at, at, you know, at Facebook back in the day, you know, I was managing online data infrastructure, okay. For Facebook from 2007 and 2015. And internally we always had this kind of culture of all the product teams building on top of the infrastructure that my team was responsible for. >>And so they were not ever, there was never a, a customer vendor relationship internally within Facebook that we're all like, we're all part of the same team. We're partnering here to have you, you know, to help you have a successful product launch. There's a very similar DNA that, that exists in Rock said, when our customers work with us and they come to us and we are there to make them successful, our consumption based pricing model also forces us to say they're not gonna really use Rock said and consume more. I mean, we don't make money until they consume, right? And so their success is very much integral part of our, our success. And so that I think is one really important angle on, you know, give us a shot, come and do an evaluation, and we will work with you to build the most efficient way to solve your problem. >>And then when you succeed, we succeed. So that I think is a very important aspect. The second one is AWS partnership. You know, we are an ISV partner, you know, AWS a lot of the time. That really helps us establish trust. And a lot of the time, one of the, the, the people that they look up to, when a customer comes in saying, Hey, what is, who is Rock? Said? You know, who are your friends? Yeah. Who are your friends? And then, you know, and then the AWS will go like, oh, you know, we'll tell you, you know, all these other successful case studies that R has, you know, you know, built up on, you know, the world's largest insurance provider, Europe's largest insurance provider. We have customers like, you know, JetBlue Airlines to Klarna, which is a big bator company. And so, so all these case studies help and, and, and, and platform and partners like AWS helps us, helps you amplify that, that, you know, and, and, and, and, and give more credibility. And last but not least, compliance matters. You know, being Soto type two compliant is, is a really important part of establishing trust. We are hip hop compliant now so that, you know, we can, you know, pi I phi data handling that. And so I think that will continue to be a part, a big part of our focus in improving the security, you know, functionality and, and capabilities that R set has in the cloud, and also compliance and, and the set of com, you know, you know, standards that we are gonna be compliant against. >>Well, I'm glad you hit on the AWS too, cause I did wanna bring that up. I, I appreciate that and I know they appreciate the relationship as well. Thanks for the time here. It's been a pleasure. Awesome. Learning about Rockette and what you're up to. Thank you. >>You bet. >>It's a pleasure. Thank you. Vi ka. All right. You are watching the cube coverage here at AWS Reinvent 22. And on the cube, of course, the leader, the leader in high tech coverage.

(upbeat music) >> Hi everybody. Welcome back to theCUBE as to continue our coverage here at AWS re:Invent '22. We're in the Venetian. Out in Las Vegas, it is Wednesday. And the PaaS is still happening. I can guarantee you that. We continue our series of discussions as part of the "AWS Startup Showcase". This is the "Global Startup Program", a part of that showcase. And I'm joined by two gentlemen today who are going to talk about what CoreStack is up to. One of them is Ez Natarajan, who is the Founder and CEO. Good to have you- (simultaneous chatter) with us today. We appreciate it. Thanks, EZ. >> Nice to meet you, John. >> And Brad Winney who is the area Sales Leader for startups at AWS. Brad, good to see you. >> Good to see you, John. >> Thanks for joining us here on The Showcase. So Ez, first off, let's just talk about CoreStack a little bit for people at home who might not be familiar with what you do. It's all about obviously data, governance, giving people peace of mind, but much deeper than that. I'll let you take it from there. >> So CoreStack is a governance platform that helps customers maximize their cloud usage and get governance at scale. When we talk about governance, we instill confidence through three layers: solving the problems of the CIO, solving the problems of the CTO, solving the problems of the CFO, together with a single pin of class,- >> John: Mm-hmm. >> which helps them achieve continuous holistic automated outcomes at any given time. >> John: Mm-hmm. So, Brad, follow up on that a little bit- >> Yeah. because Ez touched on it there that he's got a lot of stakeholders- >> Right. >> with a lot of different needs and a lot of different demands- >> Mm-hmm. >> but the same overriding emotion, right? >> Yeah. >> They all want confidence. >> They all want confidence. And one of the trickiest parts of confidence is the governance issue, which is policy. It's how do we determine who has access to what, how we do that scale. And across not only start been a process. This is a huge concern, especially as we talked a lot about cutting costs as the overriding driver for 2023. >> John: Mm-hmm. >> The economic compression being what it is, you still have to do this in a secure way and as a riskless way as possible. And so companies like CoreStack really offer core, no pun intended, (Ez laughs) function there where you abstract out a lot of the complexity of governance and you make governance a much more simple process. And that's why we're big fans of what they do. >> So we think governance from a three dimensional standpoint, right? (speaks faintly) How do we help customers be more compliant, secure, achieve the best performance and operations with increased availability? >> Jaohn: Mm-hmm. >> At the same time do the right spend from a cost standpoint. >> Interviewer: Mm-hmm. So when all three dimensions are connected, the business velocity increases and the customer's ability to cater to their customers increase. So our governance tenants come from these three pillars of finance operations, security operations and air operations at cloud operations. >> Yeah. And... Yeah. Please, go ahead. >> Can I (indistinct)? >> Oh, I'm sorry. Just- >> No, that's fine. >> So part of what's going on here, which is critical for AWS, is if you notice a lot of (indistinct) language is at the business value with key stakeholders of the CTO, the CSO and so on. And we're doing a much better job of speaking business value on top of AWS services. But the AWS partners, again, like CoreStack have such great expertise- >> John: Mm-hmm. >> in that level of dialogue. That's why it's such a key part for us, why we're really interested partnering with them. >> How do you wrestle with this, wrestle may not be the right word, but because you do have, as we just went through these litany, these business parts of your business or a business that need access- >> Ez: Mm-hmm. >> and that you need to have policies in place, but they change, right? I mean, and somebody maybe from the financial side should have a window into data and other slices of their business. There's a lot of internal auditing. >> Man: Mm-hmm. >> Obviously, it's got to be done, right? And so just talk about that process a little bit. How you identify the appropriate avenues or the appropriate gateways for people to- >> Sure. >> access data so that you can have that confidence as a CTO or CSO, that it's all right. And we're not going to let too much- >> out to the wrong people. >> Sure. >> Yeah. So there are two dimensions that drive the businesses to look for that kind of confidence building exercise, right? One, there are regulatory external requirements that say that I know if I'm in the financial industry, I maybe need to following NIST, PCI, and sort of compliances. Or if I'm in the healthcare industry, maybe HIPAA and related compliance, I need to follow. >> John: Mm-hmm. >> That's an external pressure. Internally, the organizations based on their geographical presence and the kind of partners and customers they cater to, they may have their own standards. And when they start adopting cloud; A, for each service, how do I make sure the service is secure and it operates at the best level so that we don't violate any of the internal or external requirements. At the same time, we get the outcome that is needed. And that is driven into policies, that is driven into standards which are consumable easily, like AWS offers well-architected framework that helps customers make sure that I know I'm architecting my application workloads in a way that meets the business demands. >> John: Mm-hmm. >> And what CoreStack has done is taken that and automated it in such a way it helps the customers simplify that process to get that outcome measured easily so they get that confidence to consume more of the higher order services. >> John: Okay. And I'm wondering about your relationship as far with AWS goes, because, to me, it's like going deep sea fishing and all of a sudden you get this big 4, 500 pound fish. Like, now what? >> Mm-hmm. >> Now what do we do because we got what we wanted? So, talk about the "Now what?" with AWS in terms of that relationship, what they're helping you with, and the kind of services that you're seeking from them as well. >> Oh, thanks to Brad and the entire Global Startup Ecosystem team at AWS. And we have been part of AWS Ecosystem at various levels, starting from Marketplace to ISV Accelerate to APN Partners, Cloud Management Tools Competency Partner, Co-Sell programs. The team provides different leverages to connect to the entire ecosystem of how AWS gets consumed by the customers. Customers may come through channels and partners. And these channels and partners maybe from WAs to MSPs to SIs to how they really want to use each. >> John: Mm-hmm. >> And the ecosystem that AWS provides helps us feed into all these players and provide this higher order capability which instills confidence to the customers end of the day. >> Man: Absolutely. Right. >> And this can be taken through an MSP. This can be taken through a GSI. This can be taken to the customer through a WA. And that's how our play of expansion into larger AWS customer base. >> Brad: Yeah. >> Brad, from your side of the fence. >> Brad: No, its... This is where the commons of scale come to benefit our partners. And AWS has easily the largest ecosystem. >> John: Mm-hmm. >> Whether or not it's partners, customers, and the like. And so... And then, all the respective teams and programs bring all those resources to bear for startups. Your analogy of of catching a big fish off coast, I actually have a house in Florida. I spend a lot of time there. >> Interviewer: Okay. >> I've yet to catch a big 500 pound fish. But... (interviewer laughs) >> But they're out there. >> But they're definitely out there. >> Yeah. >> And so, in addition to the formalized programs like the Global Partner Network Program, the APN and Marketplace, we really break our activities down with the CoreStacks of the world into two major kind of processes: "Sell to" and "Sell with". And when we say "Sell to", what we're really doing is helping them architect for the future. And so, that plays dividends for their customers. So what do we mean by that? We mean helping them take advantage of all the latest serverless technologies: the latest chip sets like Graviton, thing like that. So that has the added benefit of just lowering the overall cost of deployment and expend. And that's... And we focus on that really extensively. So don't ever want to lose that part of the picture of what we do. >> Mm-hmm. >> And the "Sell with" is what he just mentioned, which is, our teams out in the field compliment these programs like APN and Marketplace with person-to-person in relationship development for core key opportunities in things like FinTech and Retail and so on. >> Interviewer: Mm-hmm. >> We have significant industry groups and business units- >> Interviewer: Mm-hmm. >> in the enterprise level that our teams work with day in and day out to help foster those relationships. And to help CoreStack continue to develop and grow that business. >> Yeah. We've talked a lot about cost, right? >> Yeah. >> But there's a difference between reducing costs or optimizing your spend, right? I mean there- >> Brad: Right. >> Right. There's a... They're very different prism. So in terms of optimizing and what you're doing in the data governance world, what kind of conversations discussions are you having with your clients? And how is that relationship with AWS allowing you to go with confidence into those discussions and be able to sell optimization of how they're going to spend maybe more money than they had planned on originally? >> So today, because of the extra external micro-market conditions, every single customer that we talk to wanting to take a foster status of, "Hey, where are we today? How are we using the cloud? Are we in an optimized state?" >> Interviewer: Mm-hmm. >> And when it comes to optimization, again, the larger customers that we talk to are really bothered about the business outcome and how their services and ability to cater to their customers, right? >> Interviewer: Mm-hmm. >> They don't want to compromise on that just because they want to optimize on the spend. That conversation trickled down to taking a poster assessment first, and then are you using the right set of services within AWS? Are the right set of services being optimized for various requirements? >> Interviewer: Mm-hmm. >> And AWS help in terms of catering to the segment of customers who need that kind of a play through the patent ecosystem. >> John: Mm-hmm. Yeah. We've talked a lot about confidence too, cloud with confidence. >> Brad: Yeah. Yeah. >> What does that mean to different people, you think? I mean, (Brad laughing) because don't you have to feel them out and say "Okay. What's kind of your tolerance level for certain, not risks, but certain measures that you might need to change"? >> I actually think it's flipped the other way around now. I think the risk factor- >> Okay. >> is more on your on-prem environment. And all that goes with that. 'Cause you... Because the development of the cloud in the last 15 years has been profound. It's gone from... That's been the risky proposition now. With all of the infrastructure, all the security and compliance guardrails we have built into the cloud, it's really more about transition and risk of transition. And that's what we see a lot of. And that's why, again, where governance comes into play here, which is how do I move my business from on-prem in a fairly insecure environment relatively speaking to the secure cloud? >> Interviewer: Sure. >> How do I do that without disrupting business? How do I do that without putting my business at risk? And that's a key piece. I want to come back, if I may, something on cost-cutting. >> Interviewer: Sure. >> We were talking about this on the way up here. Cost-cutting, it's the bonfire of the vanities in that in that everybody is talking about cost-cutting. And so we're in doing that perpetuating the very problem that we kind of want to avoid, which is our big cost-cutting. (laughs) So... And I say that because in the venture capital community, what's happening is two things: One is, everybody's being asked to extend their runways as much as possible, but they are not letting them off the hook on growth. And so what we're seeing a lot of is a more nuanced conversation of where you trim your costs, it's not essential, spend, but reinvest. Especially if you've got good strong product market fit, reinvest that for growth. And so that's... So if I think about our playbook for 2023, it's to help good strong startups. Either tune their market fit or now that they good have have good market fit, really run and develop their business. So growth is not off the hook for 2023. >> And then let me just hit on something- >> Yeah. >> before we say goodbye here that you just touched on too, Brad, about. How we see startups, right? AWS, I mean, obviously there's a company focus on nurturing this environment of innovation and of growth. And for people looking at maybe through different prisms and coming. >> Brad: Yeah. >> So if you would maybe from your side of the fence, Ez from CoreStack, about working as a startup with AWS, I mean, how would you characterize that relationship about the kind of partnership that you have? And I want to hear from Brad too about how he sees AWS in general in the startup world. But go ahead. >> It's kind of a mutually enriching relationship, right? The support that comes from AWS because our combined goal is help the customers maximize the potential of cloud. >> Interviewer: Mm-hmm. >> And we talked about confidence. And we talked about all the enablement that we provide. But the partnership helps us get to the reach, right? >> Interviewer: Mm-hmm. >> Reach at scale. >> Interviewer: Mm-hmm. We are talking about customers from different industry verticals having different set of problems. And how do we solve it together so that like the reimbursement that happens, in fact healthcare customers that we repeatedly talk to, even in the current market conditions, they don't want to save. They want to optimize and re-spend their savings using more cloud. >> Interviewer: Mm-hmm. >> So that's the partnership that is mutually enriching. >> Absolutely. >> Yeah. To me, this is easy. I think the reason why a lot of us are here at AWS, especially the startup world, is that our business interests are completely aligned. So I run a pretty significant business unit in a startup neighbor. But a good part of my job and my team's job is to go help cut costs. >> Interviewer: Mm-hmm. >> So tell me... Show me a revenue responsibility position where part of your job is to go cut cost. >> Interviewer: Right. >> It's so unique and we're not a non-profit. We just have a very good long-term view, right? Which is, if we help companies reduce costs and conserve capital and really make sure that that capital is being used the right way, then their long-term viability comes into play. And that's where we have a chance to win more of that business over time. >> Interviewer: Mm-hmm. >> And so because those business interests are very congruent and we come in, we earn so much trust in the process. But I think that... That's why I think we being AWS, are uniquely successful startups. Our business interests are completely aligned and there's a lot of trust for that. >> It's a great success story. It really is. And thank you for sharing your little slice of that and growing slice of that too- >> Yeah. Absolutely. >> from all appearances. Thank you both. >> Thank you, John. >> Thank you very much, John. >> Appreciate your time. >> This is part of the AWS Startup Showcase. And I'm John Walls. You're watching theCUBE here at AWS re:Invent '22. And theCUBE, of course, the leader in high tech coverage.

>>Well, hello everybody at John Wallace here on the Cube, and glad to have you along here for day two of our coverage here at AWS Reinvent 22. We're up in the global startup program, which is part of AWS's Startup Showcase, and I've got Kevin Farley with me. He is the director of Strategic Alliances with Maria Day db. And Kevin, good to see you this morning. Good to see you, John. Thanks for joining us. Thank >>You. >>Appreciate it. Yeah. First off, tell us about Maria db. Sure. Obviously data's your thing. Yep. But to share that with some folks at home who might not be familiar with your offering. >>Yeah. So Maria DB's been around as a corporate entity for 10 plus years, and we have a massive customer base. You know, there's a billion downloads from Docker Hub, 75% of the Fortune 500. We have an enormous sea of really happy users. But what we realize is that all of these users are really thinking about what do we, what does it mean to transform it? What does cloud modernization mean? And how do we build a strategy on something we really love to drive it into the cloud and take it to the future. So what we launched about two years ago, two and a half years ago, is Skye. It's our database as a service. It leverages all the best elements, what we provide on the enterprise platform. It marries to the AWS cloud, and it really provides the best of both worlds for our >>Customers. So in your thought then, what, what problem is that solving? >>I think what you see in the overall database market is that many people have been using what we would call legacy technology. There's been lots of sort of stratification and mixes of different database solutions. All of them come with some promise, and all of 'em come with a lot of compromise. So I think what the market is really looking for is something that can take what they know and love, can bring it to the cloud and can survive the port drive the performance and scale. That completely changes the landscape, especially as you think about what modern data needs look like, right? What people did 10 years ago with the exponential scale of data no longer works. And what they need is something that not only can really deliver against their core business values and their core business deliverables, but gets 'em to the future. How do we drive something new? How do we innovate? How do we change the game? And I think what we built with AWS really delivers what we call cloud scale. It's taking something that is the best technology, and I as a V can build, marrying it to, you know, Kubernetes layer, marrying it to global availability, thinking about having true global high availability across all of your environments and really delivering that to customers through an integrated partnership. >>Could we see this coming? I mean, because you know data, right? I mean, yeah, we, we, everybody talked about the tsunami of growth, you know, >>Back 10 >>Sure. 11 years ago. But, but maybe the headlights didn't go far enough or, or, but, but you could see that there was going to be crunch time. >>There's no doubt. And I think that this has been a, there's, there's been these sort of pocket solutions, right? So if you think at the entire no sequel world, right? People said, oh, I need scale, I can get it, but what do I have to give up asset compliance? So I have to change the way I think about what data is and how I, I can govern it. So there's been these things that deliver on half the promise, but there's never been something that comes together and really drives what we deliver through CIQ is something called expand. So distributed SQL really tied to the SQL Query language, having that asset data. So having everything you need without the compromise built on the cloud allows you to scale out and allows you to think about, I can actually do exponential layers of, of data, data modeling, data querying, complete read, write, driving that forward. And I think it gives us a whole nother dynamic that we can deliver on in a way that hasn't been before. And I think that's kind of the holy grail of what people are looking for is how am I building modern applications and how do I have a database in the cloud that's really gonna support >>It? You know, you talk about distributed, you know, sequel and, and I mean, there's a little mystery behind it, isn't there? Or at least maybe not mystery. There's a little, I guess, confusion or, or just misunderstanding. I mean, I, how, nail that down a little bit. I >>Would say the best way to say it, honestly, this is the great thing, is it people believe it's too good to be true. And I think what we see over and over >>Again, you know, what they say about that. >>But this is the great part is, you know, you know, we've just had two taste studies recently with aws, with HIT labs and Certified power, both on expand, both proof in the pudding. They did the POCs, they're like, oh my God, this works. If you watch the keynote yesterday, you know, Adam had a slide that was, you know, as big as the entire room and it highlighted Samsung and they said, you know, we're doing 80,000 requests per second. So the, you know, the story there is that AWS is able as, as an entity with their scale and their breadth to handle that kind of workload. But guess what that is? That's MariaDB expand underneath there driving all of that utilization. So it's already there, it's already married, it's already in the cloud, and now we're taking it to a completely different level with a fully managed database solution. Right? >>How impressive is that? Right? I mean, you would think that somebody out there who, I mean that that volume, that kind of capacity is, is mind blowing. >>I mean, to your kind of previous point, it's like one of those things, do I see what's coming and it's here, right? You know, it's, is it actually ever gonna be possible? And now we're showing that it really is on a daily basis for some of the biggest brands in the world. We're also seeing companies moving off not only transitioning from, you know, MariaDB or myse, but all of the big licensed, you know, conversions as well. So you think about Oracle DBS Bank is one of our biggest customers, one of the largest Oracle conversions in the world onto MariaDB. And now thinking about what is the promise of connecting that to the cloud? How do you take things that you're currently doing, OnPrem delivering a hybrid model that also then starts to say, Hey, here's my path to cloud modernization. Skye gives me that bridge. And then you take it one layer farther and you think about multi-cloud, right? That's one of the things that's critical that ISVs can really only deliver in a meaningful way, is how can we have a solution for a customer that we can take to any availability zone. We can have performance, proximity, cost, proximity. We're always able to have that total data dexterity across any environment we need and we can build on that for the future. >>So if, if we're talking about cloud database and there's so many good things going forward here. You're talking about easy use and scalability and all that. But as with ever have you talked about this, there's some push and there's some pull. Yeah. So, so what's the, what's the other side that's still, you know, you that you think has to be >>Addressed? And I think that's a great question. So there's, we see that there's poll, right? We've seen these deals, this pipeline growth, this, there's great adoption. But what I think we're still not at the point of massive hockey stick adoption is that customers still don't fully understand the capabilities distributed SQL and the power they can actually deliver. So the more we drive case studies, the more we drive POCs, the more we prove the model, I think you're gonna see just a massive adoption scale. And I also think customers are tired of doing lots of different things in lots of different pockets. So neither one of the key elements of Sky SQL is we can do both transactional and analytical data out of the same database driven by the same proxy. So what, instead of having DBAs and developers try to figure out, okay, I'm gonna pull from this database here. >>Yeah. That there, it's, it's this big spaghetti wire concept that is super expensive and super time intensive. So the ability to write modern applications and pull data from both pockets and really be able to have that as a seamless entity and deliver that to customers is massive. I mean, another part of the keynote yesterday was a new deliverable, like kind of no etl. Adam talked about Aurora and Redshift and the massive complexity of what used to exist for getting data back and forth. You also have to pay for two different databases. It's super expensive. So I think the idea that you can take the real focus of AWS and US is customer value. How do you deliver that next thing that changes the game? Always utilizes AWS delivers on that promise, but then takes a net new technology that really starts to think about how do we bring things together? How do we make it more simple? How do we make it more powerful? And how do we deliver more customer value as we go forward? >>But you know, if, if I'm, I'm still an on-prim guy, just pretend I'm not saying I am. Just pretend I just for the sake of the discussion here, it's like I just can't let it go. Yeah. Right. I, I still, you know, there's control, there's the known versus the unknown. The uncertain. Yeah. So twist my arm just a little bit more and get me over the hum. >>Well, first of all, you don't have to, right? And there's gonna be some industries and some verticals that will always have elements of their business that will be OnPrem. Guess what? We make the best based in the world. It can be MariaDB, but there's those that then say, these, these elements of our business are gonna be far more effective moving to the cloud. So we give you Skye, there's a natural symbiotic bridge between everything we do and how we deliver it. Where you can be hybrid and it's great. You can adopt the cloud as your business needs grow. And you can have multi-cloud. This is that, that idea that you can, can have your cake and eat it too, right? You can literally have all these elements of your business met without these big pressure to say, you gotta throw that away. You gotta move to this. It's really, how do you kind of gracefully adopt the cloud in a way that makes sense for your business? Where are you trying to drive your business? Is it time to value, right? Is it governance? Is it is there's different elements of what matters the most to individual businesses. You know, we wanna address those and we can address >>Those. So you're saying you don't have to dive >>In, you don't have to dive >>In. You, you can, you can go ankle deep, knee deep, whatever you wanna >>Do. Absolutely. And you know, some of the largest MariaDB users still have massive, massive on-prem implementations. And that's okay. But there's elements that are starting to fall behind. There's cost savings, there's things that they need to do in the cloud that they can't do. OnPrem. And that's where expand Skye really says, okay, here is your platform. Grow as you want to, migrate as you want to. And we're there every step along the way. We, we also provide a whole Sky DBA team. Some guys just say, I wanna get outta the database world at all. This is, this is expensive, it's costly and it's difficult to be an expert. So you can bring in our DBA team and they'll man and run, they'll, they'll run your entire environment. They'll optimize it, you know, they'll troubleshoot it, they'll bug fix, they'll do everything for you. So you can just say, I just wanna focus on building phenomenal applications for my customers. And the database game as we knew it is not something that I know I want to invest in anymore. Right. I wanna make that transition >>That makes that really, yeah. You know, I mean really attractive to a lot of people because you are, you talk about a lot of headache there. Yeah. So let's talk about AWS before Sure. I let you go just about that relationship. Okay. You've talked about the platform that it provides you and, and obviously the benefits, but just talk about how you've worked with AWS over the years Yep. And, and how you see that relationship allowing you to expand your services, no pun intended. >>For sure. So, I mean, I would start with the way we even contemplated architecture. You know, we worked with the satisfactory team. We made sure that the things that we built were optimized in their environment. You know, I think it was a lot of collaboration on how does this combined entity really make the most value for our customers? How does it make the most sense for our developers as we build it out? Then we work in the, in the global startup team. So the strategic element of who we are, not all startups are created equal, right? We have, right, we have 75% of the Fortune 100, we've got over a billion downloads. So, you know, we come in with promise. And the reason this partnership is so valuable and the reason there's so much investment going forward is cuz what really, what do the cloud guys care about? >>The very, very most, they want all of these mission critical, big workloads that are on prem to land in their cloud. What do we have a massive, massive TAM sitting out there, these customers that could go to aws. So we both see, like if we can deliver incredible value to that customer base, these big workloads will end up in aws. They'll use other AWS services. And as we scale and grow, you know, we have that platform that's already built for it. So I think that when you go back to like the tenants, the core principles of aws, the one that always stands out, the one that we always kind of lean back on is, are we delivering customer value? Is this the best thing for the customer? Because we do have some competition just like many other, other partners do, right? So there is Aurora and there is rds and there is times when that's a great service for a customer. But when people are really thinking about where do I need my database to go? Where do I really need to be set for the future growth? Where am I gonna get the kind of ROI I need going forward? That's where you can go, Hey, sky sql, expand distributed sql. This is the best game in town. It's built on aws and collectively, you know, we're gonna present that to a customer. I'm >>Sold. Done. >>I love it. Right? >>Maria db, check 'em out, they're on the show floor. Great traffic. I know at at the, at the booth. They're here at AWS Reinvent. So check 'em out. Maria db. Thanks >>Kevin. Hey, thanks John. Appreciate your >>Time. Appreciate Great. That was great. Right back with more, you're watching the cube, the leader in high tech coverage.

(bright upbeat music) >> Good morning fellow cloud community nerds and welcome back to theCube's live coverage of AWS re:Invent, we're here in fabulous Las Vegas, Nevada. You can tell by my sequence. My name's Savannah Peterson and I'm delighted to be here with theCUBE. Joining me this morning is a packed house. We have three fabulous guests from AWS's global startup program. Immediately to my right is Eric. Eric, welcome to the show. >> Thank you. >> We've also got Jimmy and Jeff. Before we get into the questions, how does it feel? This is kind of a show off moment for you all. Is it exciting to be back on the show floor? >> Always, I mean, you live for this event, right? I mean, we've got 50,000. >> You live for this? >> Yeah, I mean, 50,000 customers. Like we really appreciate the fact that time, money and resources they spend to be here. So, yeah, I love it. >> Savanna: Yeah, fantastic. >> Yeah, everyone in the same place at the same time, energy is just pretty special, so, it's fun. >> It is special. And Jimmy, I know you joined the program during the pandemic. This is probably the largest scale event you've been at with AWS. >> First time at re:Invent. >> Welcome >> (mumbles) Customers, massive. And I love seeing some of the startups that I partner with directly behind me here from theCUBE set as well. >> Yeah, it's fantastic. First time on theCUBE, welcome. >> Jimmy: Thank you. >> We hope to have you back. >> Jimmy: Proud to be here. >> Jimmy, I'm going to keep it on you to get us started. So, just in case someone hasn't heard of the global startup program with AWS. Give us the lay of the land. >> Sure, so flagship program at AWS. We partner with venture backed, product market fit B2B startups that are building on AWS. So, we have three core pillars. We help them co-built, co-market, and co-sell. Really trying to help them accelerate their cloud journey and get new customers build with best practices while helping them grow. >> Savanna: Yeah, Jeff, anything to add there? >> Yeah, I would say we try our best to find the best technology out there that our customers are demanding today. And basically, give them a fast track to the top resources we have to offer to help them grow their business. >> Yeah, and not a casual offering there at AWS. I just want to call out some stats so everyone knows just how many amazing startups and businesses that you touch. We've talked a lot about unicorns here on the show, and one of Adam's quotes from the keynote was, "Of the 1200 global unicorns, 83% run on AWS." So, at what stage are most companies trying to come and partner with you? And Eric we'll go to you for that. >> Yeah, so I run the North American startup team and our mission is to get and support startups as early as inception as possible, right? And so we've got kind of three, think about three legs of stool. We've got our business development team who works really closely with everything from seed, angel investors, incubators, accelerators, top tier VCs. And then we've got a sales team, we've got a BD team. And so really, like we're even looking before customers start even building or billing, we want to find those stealth startups, help them understand kind of product, where they fit within AWS, help them understand kind of how we can support them. And then as they start to build, then we've got a commercial team of solution architects and sales professionals that work with them. So, we actually match that life cycle all the way through. >> That's awesome. So, you are looking at seed, stealth. So, if I'm a founder listening right now, it doesn't matter what stage I'm at. >> No, I mean, really we want to get, and so we have credit programs, we have enablement programs, focus everything from very beginning to hyper scale. And that's kind of how we think about it. >> That's pretty awesome. So Jeff, what are the keys to success for a startup in working with you all? >> Yeah, good question. Highly differentiated technology is absolutely critical, right? There's a lot of startups out there but finding those that have differentiated technology that meets the demands of AWS customers, by far the biggest piece right there. And then it's all about figuring out how to lean into the partnership and really embrace what Jimmy said. How do you do the co build, the co-marketing, co-sell to put the full package together to make sure that your software's going to have the greatest visibility with our customers out there. >> Yeah, I love that. Jimmy, how do you charm them? What do the startups see in working with AWS? (indistinct) >> But that aside, Jeff just alluded to it. It's that better together story and it takes a lot of buy-in from the partner to get started. It is what we say, a partner driven flywheel. And the successful partners that I work with understand that and they're committing the resources to the relationship because we manage thousands and thousands of startups and there's thousands listed on Marketplace. And then within our co-sell ISV Accelerate program, there's hundreds of startups. So startups have to, one, differentiate themselves with their technology, but then two, be able to lean in to do the tactical engagement that myself and my PDM peers help them manage. >> Awesome, yeah. So Eric. >> Yes. >> Let's say I talk to a lot of founders because I do, and how would I pitch an AWS partnership through the global startup program to them? >> Yeah, well, so this... >> Give me my sound back. >> Yeah, yeah, look for us, like it's all about scaling your business, right? And so my team, and we have a partnership. I run the North American startup team, they run the global startup program, okay? So what my job is initially is to help them build up their services and their programs and products. And then as they get to product market fit, and we see synergy with selling with Amazon, the whole idea is to lead them into the go-to market programs, right? And so really for us, that pitch is this, simply put, we're going to help you extend your reach, right? We're going to take what you know about your service and having product market fit understanding your sales cycle, understanding your customer and your value, and then we're going to amplify that voice. >> Sounds good to me, I'm sold. I like that, I mean, I doubt there's too many companies with as much reach as you have. Let's dig in there a little bit. So, how much is the concentration of the portfolio in North America versus globally? I know you've got your fingers all over the place. >> Jimmy: Yeah. >> Go for it, Jeff. >> Jimmy: Well, yeah, you start and I'll... >> On the partnership side, it's pretty balanced between North America and AMEA and APJ, et cetera, but the type of partners is very different, right? So North America, we have a high focus on infrastructure led partners, right? Where that might be a little different in other regions internationally. >> Yeah, so I have North America, I have a peer that has AMEA, a peer that has Latin America and a peer that has APJ. And so, we have the startup team which is global, and we break it up regionally, and then the global startup program, which is partnership around APN, Amazon Partner Network, is also global. So like, we work in concert, they have folks married up to our team in each region. >> Savannah, what I'm hearing is you want do a global startup showcase? >> Yeah. (indistinct) >> We're happy to sponsor. >> Are you reading my mind? We are very aligned, Jimmy. >> I love it, awesome. >> I'm going to ask you a question, since you obviously are in sync with me all ready. You guys see what you mentioned, 50,000 startups in the program? 100, 000, how many? >> Well you're talking about for the global startup program, the ISV side? >> Sure, yeah, let's do both the stats actually. >> So, the global startup program's a lot smaller than that, right? So globally, there might be around 1,000 startups that are in the program. >> Savanna: Very elite little spot. >> Now, a lot bigger world on Eric's side. >> Eric: Yeah, globally over 200,000. >> Savanna: Whoa. >> Yeah, I mean, you think about, so just think about the... >> To keep track, those all in your head? >> Yeah, I can't keep track. North America's quite large. Yeah, no, because look, startups are getting created every day, right? And then there's positive exits and negative exits, right? And so, yeah, I mean, it's impressive. And particularly over the last two years, over the last two years are a little bit crazy, bonkers with the money coming. (mumbles) And yet the creation that's going to happen right now in the market disruption is going to mirror what happened in 2008, 2009. And so, the creation is not going to slow down. >> Savanna: No, hopefully not. >> No. >> No, and our momentum, I mean everyone's doing things faster, more data, it's all that we're talking about, do more and make it easier for everybody in the same central location. Jimmy, of those thousand global startups that you're working with, can you tell us some of the trends? >> Yeah, so I think one of the big things, especially, I cover data analytics startups specifically. So, one moving from batch to real time analytics. So, whether that's IOT, gaming, leader boards, querying data where it sits in an AWS data, like companies need to make operational decisions now and not based off of historic data from a week ago or last night or a month ago. So, that's one. And then I'm going to steal one of John's lines, is data is code. That is becoming that base layer that a lot of startups are building off of and operationalizing. So, I think those are the two big things I'm seeing, but would love... >> Curious to both, Jeff, let's go to you next, I'm curious, yeah. >> Yeah, totally. I think from a broader perspective, the days of completely free money and infinite resources are coming to a close, if not already closed. >> We all work with startups, we can go ahead and just talk about all the well is just a little (indistinct)... >> So, I think it's closed, and so because of that, it's how do you deal with a lot? How do you produce the results on the go to market side with fewer resources, right? And so it's incumbent on our team to figure out how to make it an easier, simpler process to partner with AWS, knowing those constraints are very real now. >> Savanna: Yeah. >> Yeah. >> Yeah, and to build on that. I think mid stage, it's all about cash preservation, right? And it's in that runway... >> Especially right now. >> Yeah, and so part of that is getting into the right infrastructure, when you had a lot of people, suddenly you don't have as many people moving into managed services, making sure that you can scale at a cost efficient way versus at any cost. That's kind of the latter stage. Now what's really been fascinating more at the at the early stages, I call it the rise of the AIML native. And so, where you say three years ago, you saw customers bolting on AI, now they're building AI from the start, right? And that's pervasive across every industry, whether it's in FinTech, life sciences, healthcare, climate tech, you're starting to see it all the way across the board. And then of course the other thing is, yeah, the other one is just the rise of just large language models, right? And just, I think there's the hype and there's the promise, but you know, over time, like the amount of customers big and small, whom are used in large language models is pretty fascinating. >> Yeah, you must have fascinating jobs. I mean, genuinely, it's so cool to get to not only see and have your finger on the pulse of what's coming next, essentially that's what startups are, but also be able to support them and to collaborate with them. And it's clear, the commitment to community and to the customers that you're serving. Last question for each of you, and then we're talking about your DJing. >> Oh yeah, I definitely, I want to see that. >> No, we're going to close with that as a little pitch for everyone watching this show. So, we make sure the crowd's just packed for that. This is your show, as you said, you live for this show, love that. >> Yeah. >> Give us your 30 second hot take, most important soundbites, think of this as your thought leadership shining moment. What's the biggest takeaway from the show? Biggest trend, thing that has you most excited? >> Oh, that's a difficult one. There's a lot going on. >> There is a lot going on. I mean, you can say a couple things. I'll allow you more than 30 seconds if you want. >> No, I mean, look, I just think the, well, what's fascinating to me in having this is my third or fourth re:Invent is just the volume of new announcements that come out. It's impressive, right? I mean it's impressive in terms of number of services, but then the depth of those services and the building on, I think it's just really amazing. I think that the trend you're going to continue to see and there's going to be more keynotes tomorrow, so, I can't let anything out. But just the AI, ML, real excited about that, analytic space, serverless, just continue to see the maturation of that space, particularly for startups. I think that to me is what's really exciting. And just seeing folks come together, start exchanging ideas, and I think the last piece I'll do is a pitch for my own team, like we have like 18 different sessions from the North American startup team. And so, I mean, shout out to our solution architects putting those sessions together, geared towards startups for startups, and so, that's probably what I'm most excited about. >> Casual, that was good, and you pitched it in time. I think that was great. >> There you go. >> All right, Jeff, you just had a little practice time while he was going. Let's (indistinct). >> No, so it's just exciting to see all the partners that we support here, so many of them have booths here and are showcasing their technology. And being able to connect them with customers to show how advanced their capabilities are that they're bringing to the table to supplement and compliment all the new capabilities that AWS is launching. So, to be able to see all of that in the same place at the same time and really hear what they need from a partnership perspective, that's what's special for us. >> Savanna: This is special. All right, Jimmy. >> My thoughts on re:Invent or? >> Not DJ yet. >> Not DJ. Not DJ, but I mean, your first re:Invent. Probably your first time getting to interact with a lot of the people that you chat with face to face. How does it feel? What's your hot take? Your look through the crystal ball, if you want to take it farther out in front. >> I think it's finally getting FaceTime with some of the relationships that I've built purely over Chime and virtual calls over the past two years has been incredible. And then secondly, to the technical enablement piece, I can announce this 'cause it was already announced earlier, is AWS Security Lake, one of my partners, Cribl, was actually a launch partner for that service. So, a little too to the Horn for Global Startup program, one of the coolest things at the tactical level as a PDM is working with them throughout the year and my partner solution architect finding these unique alignment opportunities with native AWS services and then seeing it build all the way through fruition at the finish line, announced at re:Invent, their logo up on screen, like that's, I can sleep well tonight. >> Job well done. >> Yeah. >> Yeah. >> That's pretty cool. >> That is cool. >> So, I've already told you before you even got here that you're a DJ and you happen to be DJing at re:Invent. Where can we all go dance and see you? >> So, shout out to Mission Cloud, who has sponsored Tao, Day Beach Club on Wednesday evening. So yes, I do DJ, I appreciate AWS's flexibility work life balance. So, I'll give that plug right here as well. But no, it's something I picked up during COVID, it's a creative outlet for me. And then again, to be able to do it here is just an incredible opportunity. So, Wednesday night I hope to see all theCUBE and everyone that... >> We will definitely be there, be careful what you wish for. >> What's your stage name? >> Oh, stage name, DJ Hot Hands, so, find me on SoundCloud. >> DJ Hot Hands. >> All right, so check out DJ Hot Hands on SoundCloud. And if folks want to learn more about the Global Startup program, where do they go? >> AWS Global Startup Program. We have a website you can easily connect with. All our startups are listed on AWS Marketplace. >> Most of them are Marketplace, you can go to our website, (mumbles) global startup program and yeah, find us there. >> Fantastic. Well, Jeff, Jimmy, Eric, it was an absolute pleasure starting the day. We got startups for breakfast. I love that. And I can't wait to go dance to you tomorrow night or tonight actually. I'm here for the fist bumps. This is awesome. And you all are great. Hope to have you back on theCUBE again very soon and we'll have to coordinate on that global Startup Showcase. >> Jimmy: All right. >> I think it's happening, 2023, get ready folks. >> Jimmy: Here we go. >> Get ready. All right, well, this was our first session here at AWS re:Invent. We are live from Las Vegas, Nevada. My name is Savannah Peterson, we're theCUBE, the leader in high tech reporting. (bright upbeat music)

(bright music) >> Okay, welcome back everyone. It's theCUBE's coverage here in San Francisco, California. We're live on the show floor of AWS Summit 2022. I'm John Furrier, your host of theCUBE. And remember AWS Summit in New York city coming up this summer. We'll be there as well. And of course, re:Invent at the end of the year for all theCUBE coverage on cloud computing and AWS. The two great guests here from the APN, Global APN, Serge Shevchenko and Jeff Grimes Partner Leader. Jeff and Serge is doing partnerships. Global APN >> AWS Global Startup Program. >> Okay, say that again. >> AWS Global Startup Program. >> That's the official name. >> I love it >> Too long for me. Thanks for coming on. >> Yeah, of course. >> Yeah, appreciate it. >> Tell us about what's going on with you guys? How was you guys organized? You guys, we're obviously we're in San Francisco bay area, Silicon Valley, zillions of startups here. New York has got another one we're going to be at. Tons of startups, a lot of them getting funded, big growth in cloud, big growth in data, security, hot in all sectors. >> Jeff: Absolutely. >> So maybe we could just start with the global startup program. It's essentially a white glove service that we provide to startups that are built on AWS. And the intention there is to help identify use cases that are being built on top of AWS. And for these startups, we want to provide white glove support in co building products together, co-marketing and co-selling. Essentially, the use cases that our customers need solved that either they don't want to build themselves or perhaps more innovative. So the AWS Global Startup Program provides white glove support, dedicated headcount for each one of those pillars. And within our program, we've also provided incentives, programs, go to market activities like the AWS Startup Showcase that we've built for these startups. >> Yeah, by the way, awsstartups.com is the URL. Check it out. Okay, so your partnerships are key. Jeff, what's your role? >> So I'm responsible for leading the overall effort for the AWS Global Startup Program. So I've got a team of partner managers that are located throughout the US managing a few hundred startup ISVs right now. >> Yeah, you got a lot. >> We've got a lot. There's a lot. >> I got to ask a tough question. I'm a startup founder. I got a team. I just got my series A. We're grown and I'm trying to hire people. I'm super busy. What's in it for me? What do you guys bring to the table? I love the white glove service but translate that. What's in it for me? What do I get out of it? What's the story? >> That's a good question. Focus, I think. >> Jeff: Yeah. >> Because we get to see a lot of partners building their businesses on AWS. So from our perspective, helping these partners focus on what do we truly need to build by working backwards from customer feedback. How do we effectively go to market? Because we've seen startups do various things through trial and error and also just messaging. Because oftentimes partners or rather startups try to boil the ocean with many different use cases. So we really help them sort of laser focus on what are you really good at and how can we bring that to the customer as quickly as possible? >> Yeah, it's truly about helping that founder accelerate the growth of their company. And there's a lot that you can do with AWS but focus is truly the key word there because they're going to be able to find their little piece of real estate and absolutely deliver incredible outcomes for our customers and then they can start their growth curve there. >> What are some of the coolest things you've seen with the APN that you can share publicly? I know you got a lot going on there, a lot of confidentiality, but we're here, a lot of great partners on the floor here. I'm glad we're back at events, a lot of stuff going on, digitally with virtual stuff and hybrid. What are some of the cool things you guys have seen in the APN that you can point to? >> Yeah, absolutely. I can point to few, you can take them. So I think what's been fun over the years for me personally, I came from a startup, ran sales at an early stage startup and I went through the whole thing. So I have a deep appreciation for what these guys are going through. And what's been interesting to see for me is taking some of these early stage guys, watching them progress, go public, get acquired, and see that big day. And being able to point to very specific items that we help them to get to that point. And it's just a really fun journey to watch. >> Yeah, and part of the reason why I really love working at the AWS Global Startup Program is working with passionate founders. I just met with a founder today, he's going to build a very big business one day and watching them grow through these stages and supporting that growth, I like to think of our program as a catalyst for enterprise sort of scale. And through that we provide visibility, credibility and growth opportunities. >> A lot of partners too, what I found, talking to staff founders is when they have that milestone, they worked so hard for it. whether it's a B round, C round, or public or get bought. Then they take a deep breath and they look back at, wow what a journey it's been. So it's kind of emotional for sure, but still it's a grind. When you get funding, it's still day one. You don't stop. It's no celebrate, you got a big round or valuation. You still got to execute. >> And look it's hypercompetitive and it's brutally difficult. And our job is to try to make that a little less difficult and navigate those waters where everyone's going after similar things. >> Yeah, and I think as a group element too. I observe that startups that I meet through the APN has been interesting because they feel part of AWS. >> Serge: Totally. >> As a group of community, as a vibe there. I know they're hustling. They're trying to make things happen. But at the same time, Amazon throws a huge halo effect. That's a huge factor. You guys are the number one cloud in the business. The growth and every sector is booming. And if you're a startup, you don't have that luxury yet. And look at companies like Snowflake that built on top of AWS. People are winning by building on AWS. >> Our program really validates their technology first. So we have what's called a foundation's technical review that we put all of our startups through before we go to market. So that when enterprise customers are looking at startup technology, they know that it's already been vetted. And to take that a step further and help these partners differentiate, we use programs like the competency programs, the DevOps competency, the security competency which continues to help provide a platform for these startups, help them differentiate, and also there's go to market benefits that are associated with that. >> So let me ask the question that's probably on everyone's mind who's watching us. Actually, I asked this a lot. There's a lot of companies startups out there. Who makes the cut? Is there a criteria? God, that's not like it's sports team or anything. >> Sure. >> There's activate program, which is like there's hundreds of thousands of startups out there. Not everyone is at the APN. >> Serge: Correct. >> So ISVs, again, that's a whole nother. That's a more mature partner that might have huge market cap or growth. How do you guys focus? How do you guys focus? >> Serge: Good question. >> A thousand flowers blooming all the time. Is there a new way you guys are looking at it? I know there's been some talk about restructure or new focus. What's the focus? >> It's definitely not an easy task by any means but I recently took over this role and we're really trying to establish focus areas. So obviously a lot of the ISVs that we look after are infrastructure ISVs. That's what we do and so we have very specific pods that look after different type of partners. So we've got a security pod, we've got a DevOps pod, we've got core infrastructure, et cetera. And really we're trying to find these ISVs that can solve really interesting AWS customer challenges. >> Do you guys have a deliberate focus on these pillars? So one, infrastructure. >> Security, DevOps and data and analytics and then line of business. >> Line of business, like web marketing solutions. (group chattering) >> Yeah, exactly. >> So solutions there. >> Yeah. More solutions and the other ones are like hardcore. So infrastructure as well like storage, backup, ransomware, kind of stuff. >> Storage, networking. >> Okay, yeah, the classic. >> Database, et cetera. >> And so there's teams on each pillar. >> Yep. So I think what's fascinating for the startups that we cover is that they truly have support from a build market sell perspective. So you've got someone who's technical to really help them get the technology figured out, someone to help them get the marketing message dialed and spread, and then someone to actually do the co-sell day to day activities to help them get in front of customers. >> Probably the number one request that we always ask for Amazon is can we wish that SOC report, oh download it on the console, which we use all the time. >> Exactly. >> But security's a big deal. SREs are evolve in that role of DevOps is taking on DevSecOps. I could see a lot of customers having that need for a relationship to move things faster. Do you guys provide like escalation or is that a part of a service or not part of? >> So the partner development manager can be an escalation point, absolutely. Think of them as an extension of your business inside of AWS. >> Great and you guys, how is that partner managers measured? >> On those three pillars. >> Got it, okay. >> Are we building valuable use cases? So product development. Go to market, so go to market activities. Think blog posts, webinars, case studies, so on and so forth. And then co-sell. Not only are we helping these partners win their current opportunities that they are sourcing, but can we also help them source net new deals? >> Jeff: Yeah. >> That's very important. Top ask from the partners is get me in front of customers. Not an easy task, but that's a huge goal of ours to help them grow their top line. >> In fact, we have some interviews here on theCUBE earlier talking about that dynamic of how enterprise customers are buying. And it's interesting, a lot more POCs. I have one partner here that you guys work with on observability. They got a huge POC with Capital One and the enterprises are engaging the startups and bringing them in. So the combination of open source software, enterprises are leaning into that hard and bringing young growing startups in. So I could see that as a huge service that you guys can bring people in. >> Right and they're bringing massively differentiated technology to the table. The challenge is they just might not have the brand recognition that the big guys have. And so that's our job is how do you get that great tech in front of the right situations. >> So my next question is about the show here and then we'll talk globally. So here in San Francisco, Silicon Valley, bay area, San Francisco bay area, a lot of startups, a lot of VCs, a lot of action. So probably a big marker for you guys. So what's exciting here in SF? And then outside of SF, you guys have a global program. You see any trends that are geography-based or is it areas more mature? There's certain regions that are better. And I just interviewed a company here that's doing AWS Edge really well. It's interesting that the partners are filling a lot of holes and gaps in the opportunities with AWS. So what's exciting here, and then what's the global perspective? >> Yeah, totally. So obviously, a ton of partners from the bay area that we support, but we're seeing a lot of really interesting technology coming out of EMEA specifically. And making a lot of noise here in the United States, which is great. And so we definitely have that global presence and starting to see super differentiated technology come out of those regions. >> Yeah, especially Tel Aviv. >> Yeah. >> EMEA real quick before you get into surge. It's interesting. The VC market in Europe is hot. They've got a lot of unicorns coming in. We've seen a lot of companies coming in. They're kind of rattling their own cage right now. Hey, look at us. Let's see if they crash, but we don't see that happening. I mean, people have been predicting a crash now in the startup ecosystem for at least a year. It's not crashing. In fact, funding's up. >> The pandemic was hard on a lot of startups for sure. >> Jeff: Yeah. >> But what we've seen is many of these startups, as quickly as they can grow, they can also pivot as well. And so I've actually seen many of our startups grow through the pandemic because their use cases are helping customers either save money, become more operationally efficient, and provide value to leadership teams that need more visibility into their infrastructure during a pandemic. >> It's an interesting point. I talked to Andy Jassy and Adam Selipsky both say the same thing during the pandemic. Necessity is the mother of all invention. And startups can move fast. So with that, you guys are there to assist. If I'm a startup and I got to pivot, 'cause remember iterate and pivot, iterate and pivot so you get your economics. That's the playbook of the ventures and the models. >> Yeah, exactly. >> How do you guys help me do that? Give an example, walk me through. Pretend me I'm a startup. Hey, I am on the cloud. Oh my God, pandemic. They need video conferencing. Hey CUBE, what do I need? Serge, what do I do? >> That's a good question. First thing is just listen. I think what we have to do is a really good job of listening to the partner. What are their needs? What is their problem statement and where do they want to go at the end of the day? And oftentimes because we've worked with so many successful startups that have come out of our program, we of either through intuition or a playbook determine what is going to be the best path forward and how do we get these partners to stop focusing on things that will eventually just be a waste of time and or not provide or bring any fruit to the table, which essentially revenue. >> Well, we love startups here in theCUBE because one, they have good stories, they're on cutting edge, always pushing the envelope, and they're kind of disrupting someone else. And so they usually have an opinion they don't mind sharing on camera. So love talking to startups. We love working with you guys on our Startup Showcase, awsstartups.com. Check out awsstartups.com and check out the showcases. Final word, I'll give you guys the last word. What's the bottom line, bumper sticker for the global APN program? Summarize the opportunity for startups, what you guys bring to the table and we'll close it out. Jeff, we'll start with you. >> Totally, yeah. I think the AWS Global Startup Program's here to help companies truly accelerate their business, full stop. And that's what we're here for. >> I love it. It's a good way to put it. >> Ditto? >> Yeah. >> All right. Serge, Jeff, thanks for coming on. >> Thanks John. >> Great to see you. Love working with you guys. Hey, startups need help and the growing and huge market opportunities, the shift cloud scale, data engineering, security, infrastructure, all the markets are exploding in growth because of the digital transformation of realities here, open source and cloud. All making it happen here in theCUBE in San Francisco, California. I'm John Furrier your host. Thanks for watching. >> Let's go, John. (soft music)

>> What does it take for an entrepreneur to develop a disruptive idea, prove that it works and bring it to market. I can think of a lot of things, but one of the most important is speed. (jet engine roars) This is Dave Vellante from theCUBE inviting you to join me and John Furrier for a special CUBE on cloud startup showcase made possible by AWS. Joining theCUBE will be Michael Lebow of McKinsey. We'll also be joined by Greylock's Jerry Chen. He's going to bring the VC perspective. CIO Ben Haynes is also going to be there to lay down his practical knowledge. We'll also have Jeff Barr of AWS and together we'll feature 10 innovative companies from the AWS Global Startup Program. So if you're a technology practitioner, you'll see some of the innovations that might help transform your business. If you're an investor, you'll get a glimpse of the future and if you're an entrepreneur, you'll see how 10 companies are rocketing toward escape velocity. So join us March, 24th at 9:00 AM Pacific for theCUBE on cloud startup showcase, Innovations with Cloud Data and Cloud Ops. We'll see you there. (upbeat music)