(upbeat music) >> Live in Washington, DC. This is day two of two days of coverage. I'm John Furr, your host. We're in person face-to-face event it's kicking off day two. Dave Levy's here, Vice President of US government Nonprofit and healthcare businesses for AWS Public Sector. Dave, great to see you again, welcome back. >> Dave: Great to see you, John. >> So, great time last time we were in person, 2019, looks like the event, the last year was virtual, what's new? >> Well, first of all, I think it's just exciting. I mean, I'm excited to be back and in-person and so much has happened in our personal lives in our communities and so I'm really glad that we can all be together and it's been great so far. >> I was talking yesterday with some folks and I saw people doing some networking. I heard someone, "Hey, I'm want to hire someone." So, the face-to-face is back, we're also streaming. Max Peterson told me they're pushing it everywhere on Facebook, LinkedIn, Twitter, everywhere, Twitch, so free content, but still a lot of registrations here in person, good stuff. >> Yeah, great registrations. We're thrilled with the support from partners and customers. And also too, like you said, the connections that people are making, so it does feel good that things are flowing and people are having conversations and- >> Well, you got healthcare, nonprofits, US government, healthcare has been a big focus so far in this show. A lot of action, local governments, governments and healthcare seem to be like pandemic enabled to change. What's the update? What's the highlights so far for you? >> Well, I think the highlights are in those areas that, what we've been able to help our customers with is the ability to respond and that's what Cloud is all about and their ability to react and to respond to things that they don't necessarily know is going to happen and the big thing that none of us knew was going to happen was the pandemic. And so that ability and agility and preparedness to respond has really been great to see from a lot of those customers. >> You know, Max Peterson had the CIO from the Air Force up on stage and she's known for her comments about data and data's our data, the US Air Force and so data's big part of it. They are having a transformation and the how's that project going? What's the update there? What's your impression on that? >> Yeah, well, it was great to see the Air Force on stage and great to see Laura up there and we're really proud to support the DOD and the Air Force. And the Air Force has a lot to be proud of in their transformation journey and what they're doing with Cloud One is pretty substantial and amazing transformation for them. And then they've got 35 applications running on AWS. And so we think their progress is really good and they're thinking the right way in terms of their software factories and other types of projects. >> What's interesting is it's watching like who's adopting, it's like you look at like the pandemic has really opened up the view of the projects, which ones are doing well. And how do I say this politely? The projects that were being blocked or hidden, or the KPIs camouflaging the value were exposed because I mean, once that pulled back the curtain, people realized, "Oh my God, we're stuck," Or "we're inadequate, we are antiquated. We need to change," because now the pressure to deliver shifted to digital. I mean, this literally exposed the good, bad, and the ugly. >> It did and some were more prepared than others. There are great examples. We worked with the SBA to help expand the portal for the payroll protection program to get more lenders access faster. And that was a great project. They were able to respond really quickly and we were able to support them in that. Others, not so much. I think it you're right, it did expose that there's an opportunity. There's an opportunity to accelerate some of the things that they were doing already in terms of digital transformation. >> How about the GovCloud and the federal customers that you have, what's the traction point? How has that going? Is there a new generation here? >> GovCloud has been a great success. GovCloud it's our- >> John: 10-year anniversary. >> It's our 10-year anniversary, so we're thrilled to celebrate that. I can't believe it's 2011. >> EC2 is 15. Is that 315? I guess 15, too is SQS, the original building blocks. >> So, we've got a lot of great success through GovCloud and GovCloud was really something that was born out of what customers wanted, primarily federal customers. But we've also seen over the last few years, real adoption from regulated industry, real adoption from partners that are going into GovCloud that really want to take advantage of the security and compliance that federal customers need and the larger defense industrial base organizations need. So, GovCloud's been a fabulous success and expect I expect a lot of growth going forward. >> Yeah, is there a cultural shift in the federal government now? I can imagine some countries have been exploring this. I did talk briefly about it with Ms. Shannon Kellogg and John Wood, about how, if you're under the age of 40 and you work in the federal government, you got to be like, "Why aren't we doing this?" Like there seems to be like a cultural shift, younger generation coming in and be like, looking at the old way and be like, "Why are we still doing that?" >> Well, I think look bipartisan support for digital transformation, for making sure that we have the competitive edge for generations and generations to come in the US both in business and in defense and national security, I think is an imperative. I mean nobody I've talked to disagrees that we need to do this. And I think that younger workforce coming in behind I'm jealous of the 40-year olds, I wish I was under 40, but none of workforce really sees the obstacles that maybe previous generation saw these emerging technologies are becoming, the basic unit of computer's getting smaller, the cost to do these things is coming way down and I think that younger workforce says, "Why aren't we doing this?" >> Yeah and I think the Air Force projects are interesting too because that shows us not just about the CIA or the DOD that you have, they're leaning into production workloads, and the mission critical workloads too, the DOD is also now continuing to adopt. What else are you guys doing with the DOD? >> Well, we're partnering with GDIT on milCloud and that's going to give DOD mission owners access to a whole suite of AWS services. So, we're really excited about that. And those are available now. We're the only Cloud provider that's making that accessible to them on milCloud. And so this is going to open up the opportunity for them to start doing that mission work that you described. A good example of that are programs like ABMS, Air Force's Advanced Battle Management System. It's part of their effort around JADC2 and a great set of capabilities that they're delivering there. We're happy to have participated. We did some testing and some show intel, if you will at Ramstein Air Force Base and we're really proud to support that effort and we're excited about what the Air Force is doing. >> You know, I've always been impressed with the DOD when the tactical edge concept came out, that was very impressive because they're really using the data properly and I know Amazon has been doing well in this area because you've got things like Outpost, Wavelength, Snowball products. How's that edge piece developing? Do you see that becoming more critical now? >> It's absolutely critical. It's not becoming critical, it is critical and I think if you look at what the DOD and all of their partners are trying to accomplish, it's really moving all of that data around from the very edge in theater, back home to where it needs to be analyzed, doing it fast, doing it secure, being able to deliver on their missions and that's what this is all about. So, we see huge, huge opportunities to really innovate around the edge. >> Yeah, the data equation really is fascinating to me. Just when you think about things like words, highly available versus high availability means something 'cause you're going to want real time, not just on available data, you got to have it real time so the pressure around these projects are high. And so technically, you've got to have low latency on all this stuff. >> That's true, that's true. You've got to either have near real time or real-time availability and in many cases there's high stakes. So, the ability the DOD to pull this off is really, really important and we're a big supporter of that. >> Dave, I want to get your perspective because you've been in the industry, you've seen that the ways, we talked before cameras about the '90s and data centers and stuff. 10 years of GovCloud, look at public sector, just to look at the 10 years, interesting evolution. I mean, you couldn't give Cloud a wait 15 years ago. They weren't moving, glacier speed of adoption, now, massive adoption, uptakes there, the transformations are happening, migrations are huge, healthcare, which is like silo the data, HIPAA compliance lock everything down, everything's opening up. This is causing a lot of change. What's your reaction to that? >> Well, my reaction to that is I think customers are starting to connect what their outcomes are, whether it's a business outcome or a mission outcome or both to what Cloud can actually do. And I think that's freeing them up to make decisions about enabling Cloud in their environment, enabling experimentation, because that's what you want. You don't know what you're going to be faced with. We don't know what the threats are. We don't know if there's going to be another major pandemic. We hope there's not, but we don't know and if you set goals around your outcomes for mission and tie those, Cloud becomes such an enabler for that. And I see customers embracing that. Customers across the spectrum, nonprofit, healthcare providers, everybody, Homeland Security, VA, they're all thinking about, "What are the mission outcomes we're trying to drive?" >> Yeah, what's interesting too on that is that, just to point out is that the applications now aren't as complex to build relatively to the speed. In other words, you can get the time to value. So, the pandemic showed people that if you were in the Cloud and had that agility or optionality to be agile, you could write software 'cause software is the key in this, and not let's do the waterfall, 12-weeks assessment, 10-month rollout. Now people are doing it in 10 days, new applications. >> Sure, sure. Well, I tell customers a lot, "Think about McDonald's during the pandemic and think about customers like that who had to react to a new environment of delivery and your fast food fresh and how quickly companies like that are able to roll out capabilities." And I don't know that federal customers will be able to do it in a week or two weeks, but it's certainly possible. And it certainly will shorten that lead time that they have now in their software development. >> Well, great to see you, Dave. Is there any customers you want to highlight and you want to talk about, get a plug in for? >> Yeah, a lot of great customers here representing today and we're really appreciative also just want to say it was really great to see Max on stage for his first summit and think it was great to see Laura and others as well too. We've got some great customers coming here, The Veteran's affairs is going to be here as well as the Navy presenting on a lot of their capabilities today. So, I'm really excited about that. >> Yeah, a lot of action and education, healthcare, really blooming, really changing and modernizing. Big-wave migration, modernization, all kinds of the big wave. >> Yeah, it is. Yeah, big things coming and some of these systems are ready, so these systems are 40 and 50 years old and we're here to help these customers deliver on the agility and the extensibility of these systems to really serve citizens. >> What's your outlook for next year? What are you seeing next year so happening? How do you see everything unfolding? So you mentioned the pandemic, we're still in it, Delta Virus, who knows what's going to happen next, the world stage is changing, the global economy, space. >> I see customers really leaning in and starting to see the benefits of moving their data to the Cloud, number one, and then also to getting the insights using AI and ML to really drive the insights that they need to make the decisions on that data and I see more and more customers doing that. I did a panel this week, moderated a panel with some great customers around that and getting started is probably the biggest thing that I see and we're going to have more and more customers getting started. >> Yeah, getting into the Cloud. Congratulations to milCloud by the way, too. That was a good call out. All right, thanks for coming, I appreciate it. >> John: Yeah, thanks, Sean. >> Okay, keep coverage here. The Public Sector Summit, live in Washington, D.C. in-person event also hybrid we're streaming out. We're doing remote interviews and Amazon is streaming all the keynotes and key sessions for the digital folks out there. Thanks for watching. (upbeat music)

>> Narrator: From around the globe it's theCUBE with digital coverage of AWS reinvent 2020. Sponsored by Intel, AWS and our community partners. >> All right, you're continuing coverage of AWS reinvent 2020 virtual event. We get the pleasure of covering this show like no other AWS reinvent. We are pulling in from the other side of the world Tomer Levy, CEO of Logz.io. First time Cuber so we're going to ease them into it but it's going to be a great conversation. I'm Keith Townsend at CTO advisor. Tomer, welcome to the show. >> Keith, thank you for having me. I'm super excited to be here. >> You know what? We love having founders here on theCUBE. We have a long history of having deep conversations with builders and we're probably the show for builders. AWS reinvent is virtual. However, I think the spirit of re-invent is highlighted in companies like this. We've seen a lot of observability companies sprout up around the industry. AWS is a big, big magnet for these types of solutions. What's the assets Logz.io and how are you guys differentiating yourselves in this crowded space? >> Yeah, absolutely Keith you see observability is so fundamental to building applications on AWS that as companies develop more applications, they have to have solid observability. And we have a mission and our mission is to enable develop engineers and any engineer out there to use open source to run their observability. So when we were developers we wanted to use open source but we had to compromise on a proprietary solution. We decided to build the company so engineers can use the observability tools they're already using for logging, for metrics, for tracing, Whatever they're already using we want to enable them to use that at scale on AWS. So it's easy to use, it's super smart and the data is coordinated. And I think fundamentally it's what we're doing very differently in the market. There is no other company in the market today that takes the best open sources and bring them together as one super strong platform and we're proud to be that company. >> Well, when you say there's no other company doing open source the way that you guys are doing it, that really intrigues me especially as we look at this from the angle of Cooper Netties, the CEO of the leading virtualization company called Kubernetes, the doubts home of the internet. How do you see the intersection of opensource observability in kubernetes especially in the public cloud? >> Yeah, for sure. People say that kubernetes is almost the operating system of the future and why do people use kubernetes? They use it to make sure they can run multiple microservices. They can take their application which used to be a monolith and put it in a distributed way. So it becomes so much harder to monitor or to troubleshoot even to secure applications. So the way we built Logz.io was really designed for companies that are moving into the cloud, companies moving into kubernetes, into microservices and by having logs and metrics and traces all work together through the best open sources. I think we can help customers really get the visibility and just accelerate the software delivery. Just provide better service to their customers. >> So Levy, walk me through that journey. What is it like for a developer to come from their traditional open source roots and enter the cloud where they're melding public cloud services in AWS alongside their tools that they're using in observability. How do you help ease that transition? >> Yeah, absolutely Keith because one of the main drivers for companies adopting tools like Logz.io is actually the migration to AWS. So imagine now migration to a new ground, what do you have to think about first? Do I have the glasses? Can I see what's going on? Like when I see what's going on, I feel more confident. So if I'm now using, let's call it elk or using the open-source Grafana or using tools like Jaeger, which are all open sources too that we offer as part of our platform. So when I use these tools I'm using them to get visibility into my own application, my own infrastructure. So Logz.io faster transition to Logz.io is super easy. This is the whole notion of having an open source compatible platform. So I want to move to Loz.io, everything that worked with my open source currently still works with Logz.io but now when you move to the cloud Logz.io on AWS, we have a very strong relationship so all the services are automatically monitored. You have pre-configured dashboard, everything is interconnected so just when I jump into the AWS platform I immediately get visibility of my existing apps and of the AWS infrastructure. And that eventually helped me become confident, grow and deliver faster on AWS. >> So again this is a conference full of builders but you used the term devOps. We're starting to see a bleeding of DevOps and builders or operations and builders come together. One of the big trans and DevOps and observability is AI and machine learning. What are some of the features of AI and Machine Learning you guys are bringing to bear to this market? >> Yeah, listen I'm a big believer in AI. You know, the amount of data that companies like Logz.io have to ingest and our customers have to process. It's just something a human being cannot possibly understand. It's like billions and millions of lines of data. So this is where we bring machines to help humans. I'll give you one example, right? If you're a DevOps engineer and you see an issue in your logs, what do you do? You usually copy that and putting it into Google and you'll end up on stack overflow, maybe on GitHub, maybe on another website. What we have done is we've scraped the web and we have learned from any user on our platform. So we actually know which log line is important and which one is not. So when companies send a log line, our AI automatically scans it and says, "Hey, here are the billion log lines. No one cares about but here is one that you should really look at right now because either you know half a million people that were searching for it. There are 7,000 alerts on this and it just happened to you. Keith look, maybe you should jump in and look at that". This is where AI makes us just better operate or better DevOp people and not kind of try to replace us. >> So I'm a technical founder, you're a technical founder, theCUBE loves supporting founders. One of the advantages of being the CEO of your company is that you get to decide the culture and the mission of your company. Talk to me about the people side of your organization and how you're making a change for the better. >> Yeah, absolutely. You know, it is a privilege and to the privilege to start and come with a mission that you want to change something in the world and we were just two developers, a staff, my co-founder and myself having to use a product we didn't want to use and you know still really wanted to use an open source product. So we said let's build the company around that and this is kind of set the mission for the company as the company evolved, so is our mission. It evolves from logging to monitoring, to tracing and we also added a cloud SIEM solution all based on open source. So we're going to DevOps engineers and any engineers and we tag any engineer we tell them, "Hey, you can use the best open source tools in the cloud is one platform without compromising". And that's something that really is very differentiated today and I'm very humbled and excited to be part of this journey and I think the team at Logz.io is as well. >> You know I'm always intrigued about this journey to the cloud. Security is one of these things that intrigues me especially as we look at something as mature in the way open source. We often associate open source with public cloud, cloud native but open source is as old as technology itself. So there is a lot of practices that we bring from legacy, traditional infrastructures into the public cloud. So talk to me about that transition of security and security models? How does observability help to either take our existing tools and migrate them to the public cloud or adopt all new cloud native tools in the public cloud? >> Yeah, for sure. I think security is probably together with observability. One of the top priority that when you think about CTOs and VP of Engineering and CSOs, they're concerned about. So we've taken the observability path and bringing better glasses to our users and then on the security side there's a whole market called the SIEM market where companies look at detecting threats, investigating them and most of these tools were that companies use our legacy, incumbents and for design on their own premises world. And are not really a fit for the dynamic world of kubernetes and the cloud. And this is when we decided a couple of years ago to launch a product in that space and today this product is extremely successful. We have customers protecting their AWS environments across the board. So basically with one product for observability, you can with a single checkbox enable security and then you can detect threats. You can look at kind of the common pitfalls of AWS environment and how you can avoid them. And eventually when you see a threat, you can use our tool to investigate and find the root cause in a tool which was designed on AWS for AWS. And it's really designed for the kind of the native cloud environment rather than the on-premise as well. >> Now, is there an integration between the AI ML law of management and the threat management solutions from our observability perspective? >> Yeah, for sure. This is the beauty, it's all one data platform. So customers ship their data, loads, metrics and traces into one place and then we start to look at how can we provide more value on the data, right? How can we look at the logs from an operational perspective and tell you, "Hey, your production might be going down because of a production risks or maybe we can provide you threat intelligence". We can enrich the data and tell you, "Hey, we think you're undergoing an attack right now". So this is all done by users and it is all enraged by AI that provides more visibility, more enrichment of the data and just advice on where to look. >> So Tomer levy, CEO, founder of Logz.io. You're now a few belong. Thank you for joining the show. I hope you have a very successful AWS reinvent. Speaking of AWS reinvent, theCUBE's nonstop coverage of AWS reinvent continues. Watch some of the world's greatest builders, innovators get challenged on their vision and for us to understand and appreciate the work that's been done in this dynamic community. Continue to watch this coverage and more. Talk to you next interview on the CUBE's coverage, of AWS reinvent 2020. (soft music)

(stirring music) >> Announcer: From Seattle, Washington, it's theCUBE. Covering AWS IMAGINE Nonprofit. Brought to you by Amazon Web Services. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in downtown Seattle, Washington, actually right on the waterfront. It has been a spectacular visit here for the last couple of days. And we're back in Seattle for AWS IMAGINE. We were here a couple weeks ago for AWS IMAGINE Education. This is a different version of the conference, really focused around government and nonprofits, and we're really excited to kick off our day with the guy coming right off the keynote who's running this, he's Dave Levy. He's the vice president for U.S. Government and Nonprofit for AWS. Dave, great to see you, and congrats on the keynote. >> Thank you, thanks for having me, too. We're really excited. >> Absolutely. So as you're talking about mission and purpose, and as I'm doing my homework for some of the topics we're going to cover today, these are big problems. I couldn't help but think of a famous quote from Jeff Hammerbacher from years ago, who said, "The greatest minds of my generation "are thinking about how to make us click ads." And I'm so happy and refreshed to be here with you and your team to be working on much bigger problems. >> Yeah, well thank you. We're very excited, we're thrilled with all the customers here, all the nonprofits, all the nongovernmental organizations, all of our partners. It's just very exciting, and there are a lot of big challenges out there, and we're happy to be a part of it. >> So it's our first time here, but you guys have been doing this show, I believe this is the fourth year. >> Its fourth year, yeah. >> Give us a little background on the nonprofit sector at AWS. How did you get involved, you know, what's your mission, and some of the numbers behind. >> Well, it's one of the most exciting part of our businesses in the worldwide public sector. And we have tens of thousands of customers in the nonprofit sector, and they are doing all sorts of wonderful things in terms of their mission. And we're trying to help them deliver on their mission with our technology. So you see everything from hosting websites, to doing back office functions in the cloud, running research and donor platforms, and so it's just a very exciting time, I think. And nonprofit missions are accelerating, and we're helping them do that. >> Yeah, it's quite a different mission than selling books, or selling services, or selling infrastructure, when you have this real focus. The impact of some of these organizations is huge. We're going to talk to someone involved in human trafficking. 25,000,000 people involved in this problem. So these are really big problems that you guys are helping out with. >> They're huge problems, and at Amazon, we really identify with missionaries. We want our partners and our customers to be able to be empowered to deliver on their mission. We feel like we're missionaries and we're builders at Amazon, so this is a really good fit for us, to work with nonprofits all over the world. >> And how did you get involved? We were here a couple weeks ago, talked to Andrew Ko. He runs EDU, he'd grown up in tech, and then one of his kids had an issue that drove him into the education. What's your mission story? >> Well, on a personal level, I'm just passionate about this space. There's so much opportunity. It's everything from solving challenges around heart disease, to research for cancer, patient care, to human trafficking. So all of those things resonate. It touches all of our lives, and I'm thrilled to be able to contribute, and I've got a fantastic team, and we've got amazing customers. >> Right. It's great. Did a little homework on you, you're a pretty good, interesting guy too. But you referenced something that I thought was really powerful, and somebody interviewing you. You talked about practice. Practice, practice, practice, as a person. And you invoked Amara's Law, which I had never heard for a person, which is we tend to overestimate what we can do in the short term, but we underestimate what we can do in the long term. And as these people are focused on these giant missions, the long term impacts can be gargantuan. >> Yeah, I think so. Like you said, we're tackling some huge problems out there. Huge, difficult problems. Migrations, diseases. And, you know, it takes a while to get these things done. And when you look back on a ten year horizon, you can really accomplish a lot. So we like to set big, bold, audacious goals at Amazon. We like to think big. And we want to encourage our customers to think big along with us. And we'll support them to go on this journey. And it may take some time, but I'm confident we can solve a lot of the big problems out there. >> But it's funny, there's a lot of stuff in social now where a lot of people don't think big enough. And you were very specific in your keynote. You had three really significant challenges. Go from big ideas to impact. Learn and be curious, and dive deep. Because like you said, these are not simple problems. These aren't just going to go away. But you really need to spend the time to get into it. And I think what's cool about Amazon, and your fanatical customer focus, to apply that type of a framework, that type of way of go to market into the nonprofit area, really gives you a unique point of view. >> I hope so. And we're doing a lot of really cool things here at the conference. We've got a Working Backwards session. One of the things about working backwards that's really interesting is the customer's at the center of that. And it all starts with the customer. I can't tell you how many times I've been in a meeting at Amazon where somebody has said, wait a second. This is what we heard these customers say, this is what we heard about their mission. And it's all about what customers want. So we're really excited that our customers here and our nonprofits here are going to be going through some of those sessions, and hopefully we can provide a little innovation engine for them by applying Amazon processes to it. >> For the people that aren't familiar, the working backwards, if I'm hearing you right, is the Amazon practice where you actually write the press release for when you're finished, and then work backwards. So you stay focused on those really core objectives. >> Yeah, that's right. It's start with your end state in mind and work backwards from there. And it starts with a press release. And certainly those are fun to write, because you want to know what you're going to be delivering and how you're going to be delivering it, and frankly how your customers and how your stakeholders will be responding. So it's a really great exercise, helps you focus on the mission, and sets up the stage for delivery in the future. >> It's funny, I think one of the greatest and easy simple examples of that is the Amazon Go store. And I've heard lots of stores, I've been it now a couple times up here, in San Francisco, and the story that I've heard, maybe you know if it's true or not, is that when they tried to implement it at first, they had a lot of more departments. And unfortunately it introduced lines not necessarily at checkout, but other places in the store. And with that single focus mission of no lines, cut back the SKUs, cut back the selection, and so when I went in it in San Francisco the other day, and it gave me my little time in the store, the Google search results? It was, I think, a minute and 19 to go in, grab a quick lunch, and then get back on my way. So really laser-focused on a specific objective. >> Yeah, and that's the point of the working backwards process. It's all about what customers want, and you can refine that and continue to refine that, and you get feedback, and you're able to answer those questions and solve those difficult problems. >> That's great. Well, Dave, thanks for inviting us here for the first time again. Congrats on the keynote, and we look forward to a bunch of really important work that your customers and your team are working on, and learning more about those stories. >> Thanks, we're thrilled. Very thrilled. >> All right. He's Dave, I'm Jeff. You're watching theCUBE. We're in Seattle at the AWS IMAGINE Nonprofit. Thanks for watching, we'll see you next time. (light electronic music)

>> Voiceover: Live from Washington D.C., it's the Cube. Covering AWS Public Sector Summit. (upbeat music) Brought to you by Amazon Web Services. >> Welcome back everyone to the Cube's live coverage of the AWS Public Sector Summit here in wonderful Washington D.C. I'm your host, Rebecca Knight along with my co-host, John Furrier. We are welcoming Dave Levy to the program, he is the Vice President, Federal Government at AWS. Thank you so much for coming on the Cube. >> Yeah, thank you for having me. >> Rebecca: This is your first time, your first rodeo. >> It is my first time. >> Rebecca: Welcome. >> Glad to be here. >> You're now a Cube alumni, welcome to the Cube alumni club. >> Well exactly, right, exactly. So you have been with AWS for about two years now. AWS famously has this day one mentality. I want you to talk a little bit about the culture of the company and how the culture helps create more innovative products and services. >> Yeah, and it is always day one. You hear about that but truly working in my first two years, you really get the experience when you're here everyday, that excitement and that enthusiasm for customers. It's interesting and somebody was asking me the other day, how do you get influence inside of Amazon, how do you get you points across? And in large part because Amazon's not a PowerPoint culture, being charismatic or having some of those traits really doesn't carry the day. What really carries the day inside of Amazon is what customers want and so I can't tell you how many times in the first few years that I've been here that we have been in meetings, going through our customer working backwards process, where somebody has said, wait a minute, we heard customers say we prioritize these four things versus these three things. And that kind of sentiment carries a lot of currency inside of the business for what we prioritize and what's important to us and it's how we innovate on behalf of customers. So that's what happens everyday, it happens day one at AWS and it's been really exciting these first few years. >> That's been a great formula for Amazon. That long game as Bezos always says, Andy always says, customer first, customer-centric thinking. But this working backwards process we've learned, come to learn, it's really critical within Amazon. But also making sure customers have the right journey, right, they get what they need, they get value, lower costs, living with undifferentiated heavy lifting. I feel like I'm messaging for Amazon. (laughing) Got it memorized. I sit down and interview so many people from Amazon, I got the rap down but digital transformation is about the long game 'cause all the shifts that are going on now aren't incremental, small improvements, it's really moving the ball down the field, big time. So you're seeing major shifts within customer bases saying, like the CIA did in 2013, >> Dave: Sure. >> which was initially a hedge against big data, we heard on stage today, turned out to be a critical decision for their innovation, this modernization. Could you share some other customer experiences around this IT modernization trend that's, it's totally real, it's happening right now in D.C. in Public Sector. >> Sure, there are a lot of examples. IT modernization is something that takes on a lot of different forms and a lot of different agencies think about it in different ways but fundamentally, it's about taking the systems that are serving citizens or a war fighter and allowing for an ability and an agility to do things better and faster and cheaper and doing it in a way that continues to innovate. And you see a lot of examples of that. CMS has the 76 million records of Americans on AWS. You see large data sets starting to be hosted on AWS from agencies across the civilian sector. DOD is really starting to lean in on workloads that are traditional things like ERP. >> DOD is more than leaning in, they're really going big. There's a paper that they put out was very comprehensive-- >> Yeah, I think there's a tremendous advantage from this digital transformation and agencies are really just at the beginning of it. They're really beginning to see what flexibility it provides. I think the other thing that it's doing is it's really helping to modernize the workforce. It's allowing the IT workforce to start focusing on things that are really valuable instead of managing hardware or managing IT environment strictly. It's giving the ability to deliver solutions and that's really exciting, that's what modernization is doing. >> One of the things that comes up in the modernization talks, it's not that obvious on the mainstream press, but the whole red tape argument of government process. People process technology, again, we've done these conversations all the time but in each one, the process piece, there's red tape in all of them. People who go slower, the process has red tape in it but this idea of busting through and cutting the red tape. >> Dave: Yeah. >> All these bottlenecks, Teresa calls them blockers. >> Yeah. >> Right. That's her different word. >> Yeah, yeah. >> These are real, now people are identifying that they can be taken away, not just dealing with them. Your thoughts and reaction to that. >> Yeah, well, I agree. There's a lot of opportunity. Digitizing work flows gives you the opportunity to re-examine all of these operational processes which frankly, may have been in place for very sound reasons in the past but when you modernize and you digitize and you do it in a cloud way, you're going to start to see that some of those things and those processes that were in place, really aren't necessary any more. And it allows you to move faster, it gives you more speed and we're seeing that across customers and the US government. We're seeing it really everywhere. >> And one of the things you were saying too about the digitizing the work flow, it's really about ensuring that citizens, civilians or members of the armed forces are interacting with government in a more meaningful way. That is the overarching problem that you're trying to solve here. >> It is and it can be as simple as citizens getting the kind of content that they need from a modern website, accessing it quickly, going to higher level functions around chatbots and things like that. So these modern cloud architectures are allowing agencies to deliver services faster, deliver things to citizens in a way they haven't before. Could be citizens that need assistive technology. It's giving agencies the opportunity to do things around 508 compliance that they haven't done before. So it's really opening up the aperture for a lot of agencies on what they can deliver. >> We've been doing a lot of reporting around Jedi, the DOD, actually been following a lot of the white papers from a cloud perspective. We're not really in the political circle so we don't know sometimes whose toes we're stepping on when we poke round but one thing that's very clear from the agencies that I report, even here in the hallways this week, CIA and other agencies I've talked to, all talk about the modernization in the context of one common theme, data. Data is the critical piece of the equation and it's multifold, this single cloud with the workload objective or multiple clouds in an architecture like the DOD put out. So there's clear visibility on what it looks like architecturally, multicloud, some hybrid, some pure public cloud based on workloads, the right cloud with the right job and people are getting that. But data is evolving, the role of data 'cause you got AI which is fed by machine learning. This really is a game changer. How is that playing out in conversations that you're seeing with customers and talk about that dynamic because if you get it right, good things happen, if you get it wrong, you could be screwed. It's really one of those linchpin, core items, your thoughts. >> Every agency, virtually every agency we talk to, every customer we're talking to is saying that data is the most important thing, their data strategy. Data, you know, we've all heard the sayings, data has gravity, data is the new oil. So there's a lot of ways to characterize it but once you have the opportunity to get your data both unstructured and structured, in a place, in a cloud, in an environment where you can start to do things with it, create data lakes, you can start to apply analytics to it, build machine learning models in AI. Then you're really starting to get into delivering things that you haven't thought about before. And up until then it's been tough because the data, in a lot of our customers, has been spread out. It's been in different data centers, it's been in different environments, sometimes it's under somebody's desk. So this idea of data and data management is really exciting to a lot of our customers. >> Now a lot of people don't understand that there's also down, and this is what we're getting, we're hearing from customers as well is that, they set up the data lakes or whatever they're calling it, data strategy, data lake, whatever, then there's downstream benefits to having that data just materialize and as an anecdote to what is, you look at the Ground Station after we've had a couple great interviews here about Ground Station which I love by the way. I think that's totally the coolest thing because of the, well, the real impact is going to be great back hog, IoT is going to boom, blossom from it but it only happens because you got Amazon scale. So again, data has that similar dynamic where as you start collecting and managing it in a holistic way, new things emerge, new value emerges. >> Yeah, I would say-- >> What are some of those things that you're seeing with your customers there? >> I would say there are real-world challenges that our customers have to deal with with data, right. When you start to have volumes, terabytes, petabytes of data, they've got decisions to make. Do they expand the wall, knock out a wall and expand their data center and buy more appliances which require more heating, more cooling? Maybe they do do that but there's an alternative now. There's a place for that data to go and be safe and secure and they can start doing the things that they want to do with that data. And like you said, downstream effects. There are some things that they can do with that data that they don't even know about today, right, and Ground Station's a good example of that. >> You talk to people in the military, for example, because we just had Keith Alexander, our General, the General was on. They think tactical ads using data, save lives, protect our nation, et cetera but there's also the other benefit of it that has nothing to do with the tactical, it's a business value. The enablement is a huge conversation >> Dave: Sure. >> that you hear in these modernization trends. Not just the benefits tactically, but the enablement setup, talk about that dynamic. >> Well, you think about the data that is collected. You think about the valuable data at the VA and that has potential implications for population health and so this day is just enormously valuable. I think we're at the very beginning of what we can do with some of these things across federal and you look at agencies like Department of Interior and some of the data sets they have are just fascinating. What we can do. We've got millions of visitors to our national parks every day and we don't know what's possible with a lot of those data sets. >> Talk about some of the tools and techniques that are being used to work with that data and talk about AI and machine learning and how they have been a real game changer for some of your federal customers. >> Well, ML and AI is really, we're really at the very beginning of this transformation. I think in the fullness of time, the vast majority of applications are going to be effused with machine learning and artificial intelligence. I think that day is not too far away and they're using tools on our platform like SageMaker to make predictions in this data. And one of the great things about having a platform that has really three, different parts to the stack which are machine learning, that's where you have your frameworks. I say that's where all the really, really smart people live, all the data scientists that we're all so desperate for and then you've got that middle layer which are tools like our SageMaker which everyday developers can use. So if you've got geospatial data and you're trying to determine what's in a given area, everyday developers can use SageMaker to build machine learning models. Those are some of the things they're doing, very exciting. >> Hey, I want to get your thoughts on a comment that Teresa Carlson just made earlier today. I'm not sure she said this on camera or not but it was memorable. She said, "It used to be an aha moment with the cloud "but this year it's not, it's real, people now recognize "that cloud adoption is legit, proof is in the--" >> Rebecca: Cloud is the new normal. >> The proof is in the pudding, it's right there. You can start seeing evidence, all the doubting people out there can now see the evidence and make their own judgment, it's clear. >> Yeah. >> Cloud is of great benefit, creates disruption. As this continues to increase, and it is, numbers are there, see the business performance, what are the challenges and drivers for continued success? >> Yeah. I think the first conversation starter, so Teresa's spot on as she always is. I think the first conversation starter is always cost savings. That was the way everybody thought about the cloud in the beginning and I think there are cost savings that customers are going to realize. But I think the real value, the real reasons why customers do it is, there's an agility that happens when you move to cloud that you don't necessarily have in your other environments, there's the ability to move fast, to spin up a lot of capability in just a few minutes, in just even minutes and change the experience for users, change the experience for citizens. I think the other thing that cloud is delivering is this whole breadth of functionality that we didn't really have before. We talked about machine learning and AI but there are tools around IoT now. There's Greengrass on AWS which is simply AWS IoT inside. And places like John Deere, we have hundred thousands of telematically enabled tractors sending data back to planters. So customers are getting involved because there's this huge breadth of functionality. I think, and so that's exciting, those are the enablers, that's what's driving. I think some of the things that are getting in the way is, we've got a workforce by and large, especially in the federal government, well, this is new and that learning is happening, that enablement is happening about cloud. We're teaching about security in the cloud. It's a shared responsibility model. So it's the new normal, we know what can be done in the cloud but now there are some new paradigms about how to do it and AWS and a lot of our partners are out there talking about how to get that done. >> I want to get a double down on that because one of the things that we're doing a report on, I've been investigating, is kind of a boring topic but it's your world right on which is how Amazon bare-knuckled their way into this market through cost saving which for the federal government, I would say, is a great lead 'cause they care about cost savings. A financial institution in Wall Street might not care about cost savings. They might want arbitrage on the other side but again, government's government. You guys have earned, done the work to get all the certifications. Your team, Teresa's team has done that and now you're at the beginning of the next level. But procurement is really broken, right. I was talking to an official in an interview off the record and he said, I won't say his name till I can say it here, he said, "You know, we're living procurement in the 80s. "We still have a requirement to ship a manual "on a lot of these things." So the antiquated, inadequate procurement process is lagging so much that the technology shifts are happening in a shorter period of time. Amazon which produces thousands of new services every year and reinvents Jace's big slide thousands, next year it'll be probably 5000, who knows but it'll be a big number. That's happening, all this is happening right now, really fast but procurement's lagging behind it, really stunting the innovation equation, >> Dave: Yeah. >> the growth of innovation. Your thoughts on fixing that, how you get around it, all these old tripwire rules. >> Well, first I'll say, procurement reform is something that's on everybody's mind. This is, it's not just a blocker for cloud, it's a blocker for everybody. Technology is far outpacing what our federal government can do. So I don't, there's nobody that I talk to that thinks that we're headed in the right place with procurement reform, even our customers inside of the government. So I think what I'd say is it's really collective approach. It's an industry approach that's going to be taken to change a procurement, to help them adapt to modern laws. Do we need changes in the far perhaps, yes, but I think we need fundamental policy changes, a legislative approach to change procurement for technology. It's only going to move faster, you're right. Indie announced in 2018 I think, nearly 2000 services so you can expect there's going to be more this year. Part of that is understanding new models. Our marketplace, for example, is a way to buy and access software quickly, fast, even by the hour if necessary. That's a total-- >> Rebecca: Like Ground Station >> Yeah. >> in that way, yeah. >> By the minute if necessary. >> Yes, yes, yes. >> So it's a totally new paradigm. As far as how we're approaching now, it takes having good partners. We have good partners that are helping us with respect to contract vehicles. I think we're being transparent around how we bill, how these services translate, what's in the services that they're getting charged and I think agencies are starting to feel more comfortable with that. >> I learned a term from Charlie Bell, Engineer Lead for Amazon, did an interview, a term you guys use internally at Amazon called, dogs not barking. >> Dave: Yes. >> And it means that everyone, the barking dog everyone hears and they go after, they solve that problem. It's what you don't see, the blind spot, aka blind spots. What do you see in federal that's not barking >> Yeah, what are our dogs? >> that you're aware of? What keeps you up at night? >> What are our dogs not barking? >> John: Yeah. >> I would say, it really is our customer workforce. I think our customers really need to get enablement and training and support from us and the partner community on how to make this transition to cloud. It's incumbent upon us and it's incumbent upon the agencies to really deliver it. That does keep me up at night because this is new. This is new for, the ATO process is a little bit different. The accreditation process is different. So there's a lot of new things out there and if there's a dog that's not barking, it's somebody needs help and they're not really letting us-- >> They might not even know they need it. >> They don't know they need help or they're not saying that that they need help and they don't know where to go. >> Right. >> Right. >> They should come to you. >> Well, thanks for coming on. (laughing) >> Dave, thank you so much for coming on the Cube. >> Yeah, thank you, all right. >> Thank you, thank you. >> I'm Rebecca Knight for John Furrier. We will have more from the Cube AWS Public Sector Summit, stay tuned. (upbeat music)

>>Welcome back to Couchbase connect. My name is Dave Vellante and we're going to dig into a customer case study of sorts with two software engineers from a company called trendy all the largest e-commerce platform in Turkey. And with me are in MRA, tan Rivera, both software engineers at trendy. All welcome. Good to see you guys. Hey, before we get into the story, maybe you can tell us a little bit about trendy all. >>Let me answer that question first. Um, tri-annual uh, today is, um, 10 years old. Uh, actually, uh, it starts with them, um, e-commerce company, uh, Jen, uh, especially, uh, for clothing, uh, today, uh, it's serves several, uh, services, uh, mainly still e-commerce right. Um, we, uh, we do our business mainly on technology and we even have a say in technology, uh, technology is our main concern actually. Um, just like that actually now, >>So thank you for that. I mean, you started, I think, I think the company was founded in 2009, 2010. So you weren't, you were just, you know, kind of which we would consider the, sort of the modern era at the same time. When you look back 10 years, you know, major challenges, major advancements from a technology standpoint. So you at, at the time you had a, uh, a legacy database and you, you had a migraine, maybe you could describe the business conditions that drove you to think about actually making a change. What was the before, and then we can get into the after and what was driving that change? >>Um, maybe I could start it a bit. Well, uh, we have a recommendation domain and try new. It's like when you, when you look at a certain product, like for example, you look at a pencil, it it's commanding you, uh, any razor, uh, if you are going to buy a pink dress, it's going to recommend you a yellow dress. So if you're going to maybe buy pants, it will show you some t-shirts according to it. So, uh, since the recommendations, domain group larger, uh, we, we have struggled, uh, to keep it high scale, and it wasn't a relational DB at first, but that's even as product count increased and, uh, our right frequency increased day by day, uh, and our reef performance was affected very dramatically. Uh, I believe. Yeah. >>So you were using a traditional RDBMS, uh, and then, and, and the issue was you quite, you couldn't make the recommendations fast enough. And, you know, we always say what's real time. Real time is before you lose the customer. So you, you have to make those recommendations in time for the customer to act otherwise, you know, what do you do? Send an email after the fact, Hey, you bought this, nobody's going to pay attention to that. Right? You want to catch them in the moment. Um, and so, so what was it that, that led you to, to Couchbase and w and what was the experience of that? You know, whether it was onboarding, you know, the technology, you know, how difficult was it to get up and running to where you are today? >>Um, we were using ch Couchbase in, uh, in inter-annual, um, for several years, and we had experienced on that. Uh, and, uh, we actually, we need performance as described. So, uh, we convert our data structure to, from relational DB to, um, noise, Carol Levy, um, them actually on our recommendation, uh, platform, the main problem was, uh, invalidation process. You know, um, we are selling things and, um, in seconds they can be sold out and we, we shouldn't be recommend them anymore. And we are, we are keeping track of this by invalidation process and relational DB writing those data to our relationship Libby was, uh, was taking two, two minutes too much time. And, um, by changing this structure to, uh, pathways, we, we, we see that benefits, uh, and it takes so, so, uh, uh, short time, actually, >>I'm so sorry if, if I can just clarify w what was taking a long time, the, the updating the actual records, so that you could actually inform a customer that it was out of stock, or was it the coding that was too complicated? >>Well, it was, it was not because, um, there are millions of products intangible, and, uh, those issues are coming huge, actually. So we are keeping track of time if it's sold out or it's, it can be sellable, uh, when, when a product, uh, detail is seen by the customers, we are recommending some other products too, but those other products must be sellable too. So the main, the main problem was that, and, uh, we are writing them in our relational DB. There is a huge rights law actually. So it was not coding. It was the amount of data actually. >>Okay. And so it was the update intensity, um, within the database and the ability of the database to actually return accurate results quickly. So what was the after, like, uh, can you talk about sort of the, the business impact? What were the, the improvements that you've experienced? >>Yeah. Maybe I can ask her that, uh, like parties said that the main reason we switched is because that, uh, there are so many products coming near in trend, and many of them are being stopped being sold out and the updates to it, it was on a relational, the vendor rights, or too much that you couldn't, uh, dur customers that fast reply because the database was getting effected by the amount of high rights. Because when you think about it, there are millions of products coming, and there are millions of rights, uh, operations on the database. So those affecting the reach performance. So, uh, it, it could occur to you that when you click on a product, you would see maybe as took out product as a recommendation, or maybe a product that is not in the website anymore. So, uh, when we switched to, uh, Couchbase that, uh, we saw that, uh, it's using less resources, which, uh, using less posts, active, alive, and it's also, uh, giving responses faster. >>The main reason, uh, we were using relational DB at first was the invalidation process like five. He said, because it was, we had a consumer that was listening to messages, uh, the innovation messages, and then, uh, and then the writing them into database. But, uh, in the part, uh, it meant that actively writing to database that for every product document that you would need to update the document, but for, uh, for, for, uh, for relational DB, it would be vetoed easier to just make this product, uh, every available, false, or true. So that's why we were sticking with relationship with DB at first. And that's why we made it that first as a relational DB, but as time increased and our product count, and our sellers increased, we realized that, uh, we should find another solution to the invalidation process, and we should, uh, switch because, uh, I mean, it CA it has come to a point at one point that it would just maybe, uh, take a solid, so much time that, uh, we were scaling our consumers at nighttime to just not affect daily users anymore. >>Uh, so that's why that's the main reason we switched. And, uh, after switching, we had in, uh, like I said, the response time and high write throughput, and also one of the reasons is also because that the, uh, the application that was with the use of Couchbase because, uh, since strangled is growing larger than our main data centers. And, uh, like we can see that every day, sometimes we deploy our, uh, apps to yet another cluster. And we, that's why we sometimes need to have backups or different data centers, and Couchbase was providing very good relations, very good solutions to this, which is. Yeah. That's why we switched actually. So we asked >>Couchbase running it's if I understand it, it's running the recommendation engine. And do you still use a traditional RDBMS for the transaction system or is Couchbase doing both? >>Yeah, okay. Uh, we are, uh, actually inter-annual, we are in discovery a team, actually, we call it tribe and in discovery, tribe, uh, relational DB, I think, uh, now, uh, very small, uh, small, uh, teams are using it. Um, it's personally just very low actually. Uh, but, uh, other other tribes, for example, orders, checkout, and maybe, uh, uh, promotions, uh, something like other teams are still using RDBMS, but in discovery team, it's very important to serve customers very fast. We need to show them the products immediately. We need to personalize them. Uh, we sh we should, uh, show them, uh, related products in the meantime, in real time, actually. So in this current Stripe, we are, um, barely using it, uh, RDBMS systems, actually. >>How hard was it to migrate from the RDBMS? Because you hear a lot of stories about how difficult that is to do. You've got to freeze the code, you bringing up new code, you've got to synchronize the functionality. How did you manage that? >>Well, to be honest with you, just ask the data science team to just send the products. Uh, at the same time, we were like, we were keeping the legacy API open that the clients were still coming there. And, um, to be honest, there were lots of legs on that, too. So even if, uh, the, the newer products came a bit later, uh, it shouldn't be seen because it was always coming late. So, uh, we had, we made a new API that is connecting to Couchbase and we wanted the data science team to start feeding it, but we asked the clients to switch it by time. I mean, we were still supporting the old one, but, uh, when we, when we asked the clients to switch to the new API, we just closed the last one. So we didn't really migrate any data to be honest. Like we, we, it was from scratch. And since it's a, it's a recommendation domain, uh, we believe it's better to, uh, add data's from scratch because in our new domains, we are storing them in documents. They are always sending a new list to us. So that's how it gets updated all the time. So since it's not a user related data, it wasn't really like a migration process. >>Is this is part of the secret sauce that you're doing. Schema lists, no schema on, right to Couchbase. And is that correct? And how are you handling it? I'm like, how are you getting that awesome write performance? >>Well, the main reason we believe is that, uh, before, when it was relational DB, like for example, loan product to one product and a second product to first product, third product, first of all, that like you were duplicating the records so that when the product gets removed, uh, from, from a product recommendation, or maybe one of, if a product is getting invisible, for any reason, it should be removed, or maybe it could be a stockout that it means it's not that for every record, you are sending your records for invalidation, but in our new system, it means that this, uh, for this content, there are 24 contents let's say, and like four of them that's finished. It's not there. It's okay. You're just replacing the whole list so that you are not duplicating the records. I mean, this is not like first product first and first, the second, and first to third, and first changes you are replicating this, this change three times, like a delete, uh, product one from three, three product, one from two, and you are deprecating the deletion record, but now we are just replacing the list. So you are doing that all of the operation in 1, 1, 1, uh, Kafka queue message. If I should be able, if I was able to, uh, tell about it. So it's a bit hard to explain it in, uh, in speech, but, uh, we have a nice graphic that's showing how we are doing it now. >>That makes sense. Okay. Thank you for that. And so, as you think about, you're modernizing your application infrastructure, where are you at today? How do you see this modernization effort going forward >>Actually, um, today, uh, we are mainly looking for, um, cross cluster replication. Uh, all our products are, uh, uh, deployed, uh, different clusters and different geographical locations. Uh, we, we always using ch um, we try to always use, um, modern products and, uh, uh, try to avoid, uh, old relational databases, especially for our discovery. Right. And, uh, my mandala is modernizing it, uh, all, uh, engineer's keeping up to date with recent technologies and, uh, our customers are happier. They are not seeing some glitches, some, uh, rates, uh, or while they're using our products. >>Okay. So maybe I could double click on that. So, cause you mentioned the impact of customers and I'm interested in your organizational impact and what it means for you internally, but, but when you talk about cross cluster replication, is that to scale, uh, is that a performance impact? Is that for availability? What's the impact of that effort? That modernization effort? >>Uh, I believe it's, it's all, uh, main reason is availability. I believe. Uh, like we can't know when a cluster can go down, we can't be sure about it, uh, in a, in a system we can, but that we should be up and running all the time. And, uh, there should be some, uh, some backups that, uh, that can switch when a cluster goes down. But also the main reason, uh, well, one of the main reasons is to be able to scale because, uh, the, the clusters that we had wasn't enough, uh, considering our user base. So, uh, let's say you want to even extend your user base, but, uh, like the cluster is being a bottleneck to you because you can't get that much users, but, uh, when you do post cluster that you have backup and you have scalability and it's, uh, considering how new considering if the machines are newer, maybe faster response times. I don't know, uh, maybe, uh, network part would know that better, but, uh, yeah, but all of them, I will leave. >>Great guys. Well, thank you so much for sharing your story, uh, uh, MRA and Fati. Uh, appreciate you guys coming on the cube. >>Thanks a lot. Yeah. Thanks. Thanks. Thank you for, uh, hosting. >>Yeah, it's our pleasure. And thank you for watching. Couchbase connect online on the cube, keep it right there for more great content from the event.

>>From the cube studios in Palo Alto in Boston. It's the cube covering the IBM thing brought to you by IBM. Everybody we're back. This is Dave Vellante the cube, and this is our wall-to-wall coverage, IBM's digital thing experienced for 2020. We're really excited to have Jerry Cuomo on. He's the, uh, vice president of blockchain technologies and an IBM fellow and longtime cube alum. Jerry, good to see you again. Thanks for coming on and wish we were face to face, but yeah, this'll do. Good to see you too. Yes, thanks for having me. So we've been talking a lot of and talking to, I've been running a CEO series a, of course, a lot of the interviews around, uh, IBM think are focused on, on COBIT 19. But I wonder if you could start off by just talking a little bit about, you know, blockchain, why blockchain, why now, especially in the context of this pandemic. >>David's, it's as if we've been working out in the gym, but not knowing why we needed to be fixed. And I know now why we need to be fit. You know, blockchain is coming just in time. Mmm. You know, with the trust factor and the preserving privacy factor. Okay. The way we move forward the world is now becoming more digital than ever people working from home. Um, the reliance and online services is, that's critical. our ability to work as a community accompanies companies. The shared data is critical. you know, blockchain brings a magical ingredient and that's the ingredient of trust, you know, in sharing data. Okay. When, if that data and the sources that are providing that data arc okay. From verified and trusted, we're more likely to use that data and you the, any friction that's caused for fear of trepidation that the data is going to be misused. >>Mmm. It goes start to go away. And when that happens, you speed up an exchange and we need speed. Time is of the essence. So blockchain brings a platform for trusted data exchange while preserving privacy. And that provides a foundation. I can do some amazing things in this time of crisis, right? Yeah. And it's, it's not only trust, it's also expediency and you know, cutting out a lot of the red tape. And I want to talk about some of the applications. You're heavily involved in that in the distributed ledger, a project, you know, one of the early leads on that. Um, talk about some of the ways in which you're flying that distributed a ledger. And let's go into some of the examples. So we're, we're really fortunate to be an early adopter blockchain and, and provider of blockchain technology and kind of the fruit of that. >>Um, as I said, it couldn't happen any sooner where we have, Mmm, I would say over a thousand, alright. Users using IBM blockchain, which is powered by the opensource Hyperledger fabric, I'd say over a hundred of those users, um, have reached a level of production networks. you know, it's been great to see some of the proprietors of those networks now repurpose the networks towards hastening the relief of, uh, and one, a couple of examples that stand out, Dave. Mmm. You've seen what's happening to our supply chain. And then I think we got some rebound happening as we speak, but companies all of a sudden woke up one morning and their supply chains were, I'm exhausted. So suppliers, we're out of key goods and the buyers needed very rapidly to expand. They're, the supplier is in their, in their supply chain. there are laws and regulations about what it takes to onboard a new supplier. >>You want to make sure you're not onboarding bad actors. So in IBM for example, we have over 20,000 suppliers to our business and it takes 30 to 40 days who, uh, validate and verify one of those suppliers. We don't have 30 to 45 days, you know, think about you're a healthcare company or a food company. So working with a partner called Jane yard, uh, co-created a network called trust yourself buyer. And we've been able to repurpose, trust your supplier now or companies that are looking, you know, around Kobe 19 to rapidly okay, expand, you know, their, their supply chain. So if you imagine that taking us 45 days or 40 days to onboard a new supplier, okay. Pick, pick a company in our supply chain, Lenovo, that supplier may very well want to go to Lenovo to and provide services to them. Well guess what, it's going to take 40 days, the onboard to Lenovo. >>But if they're part of the trust or supplier network and they've already onboarded to IBM, they're well on their way. You're being visible to all of these other buyers that are part of the IBM network, like Lenovo and many others. And instead of taking 40 days, maybe it only takes five days. All right. So radically, radically, you know, improving the time it takes them. You know, with companies like Ford making ventilators and masks, it will kind of be able to onboard Ford into, you know, health care, uh, companies. But you know, we want to be able to do it with speed. So trust your supplier is a great use of blockchain. Two, expand a buyer and suppliers. Mmm. Exposure. Mmm. And they expand their network to quickly onboard. And you know, with the trust that you get an exchanging data from blockchain with the Mmm provenance, that Hey, this company information was truly vetted by one of the trusted members of the network. >>There's no fee or trepidation that somehow these records were tampered with or, or misused. So that's one example they have of using blockchain. That's a huge, uh, example that you gave because you're right, there are thousands and thousands of companies that are pivoting to making, like you said, ventilators and masks and yeah, they're moving so fast and there's gotta be a trust involved. On the one hand, they're moving fast to try to save their businesses or you know, in the case of Ford, you help save the, the country or the world. On the other hand, you know, there's risks there. So that, that helps. I want to understand me. Pasa basically is, if I understand it, you can privately share, uh, information on folks that are asymptomatic but might be carriers of covert 19. Am I getting that right on? Okay. So me Pasa starts as a project, uh, from a company called has Sarah and their CEO Jonathan Levy. >>And among other things, Jonathan Levy is an amazing, uh, software developer and he's helped us and the community at large, bill, the Hyperledger fabric, uh, blockchain technology, that's part of IBM. Mmm. The power is IBM blockchain. So Jonathan, I have this idea because w what was happening is there were many, many data sources, you know, from the very popular and well known, uh, Johns Hopkins source. And we have information coming from the weather company. There are other governments, um, putting out data. Jonathan had this, this idea of a verified Mmm. Data hub, right? So how do we kind of bring that information together in a hub where a developer can now to get access to not just one feed, but many feeds knowing that both the data is an a normalized format. So that's easy to consume. And like if you're consuming 10 different data sources, you don't have to think about 10 different ways to interact it. >>No kind of normalizing it through a fewer, like maybe one, but also that we really authentically know that this is the world health organization. This is indeed John Hopkins. So we have that trust. So, okay. Yeah. With me, Pasa being I'm a data hub four, uh, information verified information related to the Kronos virus, really laying a foundation now for a new class of applications that can mash up information to create new insights, perhaps applying Mmm. Artificial intelligence machine learning to really look not just at any one of those, uh, data sources, but now look across data sources, um, and start to make some informed decisions. No, I have to say operate with the lights on, uh, and with certainty that the information is correct. So me Pasa is that foundation and we have a call for code happening that IBM is hosting for developers to come out and okay. Bring their best ideas forward and X for exposing me Pasa as a service to the, in this hackathon so that developers can bring some of their best ideas and kind of help those best ideas come alive with me. Me has a resource. >>That's great. So we've got two, we got the supply chain, we just need to share the Pasa. There's the other one then I think we can all relate to is the secure key authentication, >>which I love. >>Uh, maybe you can explain that and talk about the role that blockchain >>we're launching fits, right. So you know, there is people working from home and digital identity verification. It is key. You know, think about it. You're working remotely, you're using tools like zoom. Um, there's a huge spike in calls and online requests from tele-health or government benefits programs. Yeah. So this is all happening. Everything behind the scenes is, yeah. Around that is, is this user who they say they are, is this doctor who they say they are, et cetera. And there are scams and frauds out there. So working with speed, it means working with certainty. and with the verified me networks set out to do a couple of years ago and the beautiful part is, you know, it's ready to go now for this, for this particular usage it's been using. Mmm. Basically think about it as my identity is my identity and I get to lease out information too different institutions to use it for my benefit, not necessarily just for their benefit. >>So it's almost like digital rights management. Like if you put out a digital piece of art or music, you can control the rights. Who gets to use it? What's the terms and conditions, um, on, on your terms? So verified me, um, allows through a mobile app users to invite institutions who represent them, verify them. No. And so I'll allow my department of motor vehicle and my employer, Mmm. Two to verify me, right? Because I want to go back to work sooner. I want to make sure my work environment, um, I'm making this up. I want to make sure my work environment, the people have been tested and vaccinated, but I don't want to necessarily, you know, kind of abuse people's privacy. Right? So I'll opt in, I'll share that information. I'll get my, my doctor and my, uh, department of motor vehicle to say, yes, this is Gary. >>He's from this address. Yes, he has been vaccinated and now I can kind of onboard to services as much quicker whether that service is going through TSA. Do you get on an airplane badging back into my office or you know, signing on to a, you know, telemedicine, a service or government, a benefits program, et cetera. So verify me is using the self, uh, at the station through a mobile application to help speed up the process of knowing that that is truly you and you truly want this service. Uh, and you are also calling the shots as to that. What happens with your information that, you know, it's not spread all over the interweb it's under your control at all time. Right. So I think it's the best of all worlds. The national Institute for standards and technology looked at, verified me. They're like, Oh my gosh, this is like the perfect storm of goodness for identity. >>They actually appointed, yeah, it has a term, it's called triple blind data exchange. It sounds like a magical act. A triple blind data exchange means the requester. Mmm. Doesn't know who the provider is and less know the requester. Um, allows the provider to know, Mmm, the provider doesn't know who the requester requested, doesn't know who the prior provider is that is double-blind. And then the network provider doesn't know either. Right. But somehow across disformed and that's the magic of blockchain. I'm allowing that to happen and with that we can move forward knowing we're sharing information where it matters without the risk of it leaking out to places we don't want to do. So great application of secure key and verified me. Yeah, I love that. Then the whole concept of being able to control your own data. You hear so much today about, you know, testing and in contact tracing using mobile technology to do that. >>But big privacy concerns. I've always felt like, you know, blockchain for so many applications in healthcare or just being able to, as you say, control your own data. I want to better understand the technology behind this. When I think about blockchain, Mmm. I obviously you don't think about it. Cryptography, you've mentioned developers a number of times. There's software engineering. Yeah. Distributed ledger. Um, I mean there's, there's game theory in the, in the, in the cryptocurrency world, we're not talking about that, but there's the confluence of these technologies coming to them. What's the technology underneath these, these applications? Talking about it there, there is an open source, an organization called Hyperledger. It's part of the Linux foundation. They're the gold standard and open source, openly governed, Mmm. Technology you know, early on in 2018 yep. 18, 26. I mean, we got involved, started contributing code and developers. >>Two Hyperledger fabric, which is the industry's first permissioned blockchain technology. Permission meaning members are accountable. So the network versus Bitcoin where members are anonymous and to pass industry Reggie regulations, you can't be anonymous. You have to be accountable. Um, that's not to say that you can't, okay. Work privately, you know, so you're accountable. But transactions in the network, Mmm. Only gets shared with those that have a need, need to know. So that the foundation is Hyperledger fabric. And IBM has a commercial offering called the IBM blockchain platform that embodies that. That kind of is a commercial distribution of Hyperledger fabric plus a set of advanced tools to make it really easy to work with. The open source. All the networks that I talked about are operating their network across the worldwide IBM public cloud. And so cloud technology lays a really big part of blockchain because blockchains are networks. >>Mmm. You know, our technology, IBM blockchain platform runs really well in the IBM wow. But it also allows you to run anywhere, right? Or like to say where it matters most. So you may have companies, I'm running blockchain nodes in the IBM cloud. You may have others running it on their own premises behind their firewall. You might have others running an Amazon and Microsoft Azure. Right. So we use, um, you may have heard of red hat open shift, the container technology so that we can run Mmm. Parts of a blockchain network, I guess they said where they matter most and you get strengthened a blockchain network based on the diversity of the operators. Because if it was all operated by one operator, there would be a chance maybe that there can be some collusion happening. But now if you could run it know across different geographies across the IBM cloud. >>So almost three networks all run on use this technology or run on the IBM cloud. And Dave, one more thing. If you look at these applications, they're just modern application, you know, their mobile front ends, their web portals and all of that kind of, okay. Okay. The blockchain part of these applications, usually it's only 20% of the overall endeavor that companies are going through. The other 80% it's business as usual. I'm building a modern cloud application. So what we're doing in IBM with, but you know, red hat with OpenShift with our cloud packs, which brings various enterprise software across different disciplines, blends and domains like integration, application, data, security. All of those things come together to fill the other 80% the above and beyond blockchain. So these three companies, okay. You know, 99 plus others are building applications as modern cloud applications that leverage this blockchain technology. So you don't have to be a cryptographer or you know, a distributed database expert. It's all, it's all embodied in this code. Mmm. Available on the IBM cloud, 29 cents a CPU hour. It was approximately the price. So it's quite affordable. And you know, that's what we've delivered. >>Well, the thing about that, that last point about the cloud is it law, it allows organizations, enterprises to experiment very cheaply, uh, and so they can get, uh, an MVP out or a proof of concept out very quickly, very cheaply, and then iterate, uh, extremely quickly. That to me is the real benefit, the cloud era and the pricing model. >>I just mentioned, David, as I said it when I started, you know, it's like we were working out in a gym, but we weren't quite sure. We knew why we were, we were so keen on getting fit. And what I see now is this, you know, blossoming of users who are looking at, you know, a new agreement. We thought we understood digital transformation. Mmm. But there's a whole new nice to be digitized right now. You know, we're probably not going to be jumping on planes and trains, uh, working as, as, as more intimately as we were face to face. So the need for new digital applications that link people together. Uh, w we're seeing so many use cases from, um, trade finance to food safety, to proxy voting for stock, know all of these applications that we're kind of moving along at a normal speed. I've been hyper accelerated, uh, because of the crisis we're in. So blockchain no. Couldn't come any sooner. >>Yeah. You know, I want to ask you, as a technologist, uh, you know, I've learned over the years, there's a lot of ways to skin a cat. Um, could you do the types of things that you're talking about without blockchain? Um, I'm, I'm sure there are ways, but, but why is blockchain sort of the right path, >>Dave? Mmm. You can, you can certainly do things with databases. Mmm. But if you want the trust, it's as simple as this. A database traditionally has a single administrator that sets the rules up for when a transaction comes in. Mmm. What it takes to commit that transaction. And if the rules are met, the transactions committed, um, the database administrator has access who commands like delete and update. So at some level you can never be a hundred percent sure that that data was the data that was intended in there. With a blockchain, there's multiple administrators to the ledger. So the ledger is distributed and shared across multiple administrators. When a transaction is submitted, it is first proposed for those administrators, a process of consent happens. And then, and only then when the majority of the group agrees that it's a valid transaction, is it committed? And when it's committed, it's committed in a way that's cryptographically linked two other transactions in the ledger, I'm making it. >>Mmm tamper-proof right. Or very difficult to tamper with. And unlike databases, blockchains are append only so they don't have update and delete. Okay. All right. So if you really want that center of trusted data that is a tested, you know, that has checks and balances across different organizations, um, blockchain is the key to do it, you know? So could you do it in data with a database? Yes. But you have to trust that central organization. And for many applications, that's just fine. All right. But if we want to move quickly, we really want to share systems of record. Mmm. I hear you. Sharing a system of record, you have regulatory obligations, you can say, Oh, sorry, the record was wrong, but it was put in there by, by this other company. Well, they'll say, well, >>okay, >>nice for the other company, but sorry, you're the one in trouble. So with a blockchain, we have to bring assurances that we can't get into that kind of situation, right? So that shared Mmm. Distributed database that is kind of provides this tamper resistant audit log becomes the Colonel cross. And then with the privacy preservation that you get from encryption and privacy techniques, um, like we have like these things, both channels, um, you can transact, um Hm. And be accountable, but also, Mmm. Only share of transactions with those that have a need to know, right? So you get that level of privacy in there. And that combination of trust and privacy is the secret sauce that makes blockchain unique and quite timely for this. So yeah, check it out. I mean, on the IBM cloud, it's effortless. So to get up and running, you know, building a cloud native application with blockchain and you know, if you're used to doing things, um, on other clouds or back at the home base, we have the IBM blockchain software, which you can deploy. Yeah. Open shift anywhere. So we have what you need in a time of need. >>And as a technologist, again, you're being really, I think, honest and careful about the word tamper. You call it tamper resistant. And if I understand it right, that, I mean, obviously you can fish for somebody's credentials. Yeah. That's, you know, that's one thing. But if I understand that, that more than 50% of the peers in the community, it must agree to tamper in order for the system. You tampered with it. And, and that is the beauty of, of blockchain and the brilliance. Okay. >>Okay. Yeah. And, and, and for, um, performance reasons we've created optimizations. Like you can set a consensus policy up because maybe one transaction it's okay just to have a couple people agree and say, Oh, well, you know, out of the a hundred nodes, Mmm. Three agree, it's good enough. Okay. Other, other policies may be more stringent depending on the nature of the data and the transaction, right? So you can tone, you can kind of tune that in based on the class of transaction. And so it's kind of good and that's how we can get performance levels in the, you know, thousand plus. In fact, IBM and RBC, um, recently did, um, a series of performance analysis because RBC said, Hey, can I use this for some of my bank to bank exchanges and we need to support over a thousand transactions per second. They were able, in their use case, there's support over 3000. Transact for a second. Okay. Mmm. You know, that we were very encouraged by that. I'm glad you clarified that because, so essentially you're saying you can risk adjust the policies if you will. >>That's great to know. Mmm. I could go on forever on this topic. Well, we're unfortunately, Jerry, we're well over our time, but I want to thank you for coming back, planning this important topic. Thrilled. IBM has taken a leadership position here, and I think, you know, to your point, this pandemic is just going to, can accelerate a lot of things and blockchain is, but in my view anyway, one of them. Thank you, Dave. Oh, great questions and I really appreciate it. So everyone out there, um, stay safe. Stay healthy. All right. Thank you Jerry, and thank you for watching everybody. This is Dave Volante for the cube. Our coverage of the IBM think digital 2020 event. We'll be right back. Perfect. The short break.

>> From Seattle Washington, it's theCUBE, covering AWS Imagine, nonprofit. Brought to you by Amazon Web Services. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're actually on the waterfront in Seattle at the AWS Imagine nonprofit event. We were here a couple weeks ago for the AWS Imagine education event. This is really about nonprofits and solving big, big problems. So Dave Levy and team have you know dedicated to some of these big problems. And one of the big problems in the world is human trafficking, and problems that people are encountering and all kinds of nasty situations all over the world. And we're really excited to have someone who's tackling that problem, and really trying to bring a voice to those people that wouldn't otherwise have a voice. And she's Hend Alhinnawai, she's the CEO of Humanitarian Tracker. Hend, good to see you. >> Thank you Jeff, good to be here. >> Absolutely. So before we jump into it, impressions on this event? >> Wonderful event bringing together technologists, people in nonprofits, really creating synergies for people to collaborate and talk to each other and network and learn how they can advance their organizations. >> Such important work. >> Yes. >> So give us kind of the background on what you're up to, what Humanitarian Tracker's all about. >> So Humanitarian Tracker's a nonprofit forum. It was created to connect and empower citizens using innovation and technology, but specifically for humanitarian events. We were among the first to combine crowdsourced reports with data mining and artificial intelligence and apply them to humanitarian disasters, conflicts, human rights violations, disease outbreak. All the way to tracking the UN's Sustainable Development Goals. Really giving a holistic view of what's happening. >> It's interesting, you know, it's probably like the middle eastern spring, I can't remember the exact term that people use, where it was kind of the first use of regular people using their mobile phones to kind of grab a ground swell of action. You're not looking at the politics specifically, you're looking more at humanitarian disasters. But pretty amazing kind of what a connected phone represents to anyone anywhere in the world now to communicate what's happening to them. To share that story. We really didn't have anything like that before. To get that personal event on the ground. >> No it's really a new way of consuming, creating and consuming information. So the cell phone has really given people on the ground a chance to tell their own story. But it's not enough. If you have an event that happens to you. Something happens to you. And you record it, it stops there. But the unique thing with Humanitarian Tracker is it gives people that forum to show the world and tell them what's happening to and around them. >> Right, but it's not just about the individual. And what you guys are doing is using cutting edge technology, obviously you're here as part of the AWS event. In terms of machine-learning and big data to grab a large number of these reported events and distill it into more of an overarching view of what is actually happening on the ground. How did you do that, where did you get that vision, how are you executing that? >> Well, we're all about empowering the citizen. And in our line of work we deal with a lot of data, a lot of information, most of it is unstructured, most of it is crowdsourced. So we use machine-learning to help us extract important details. Information on time. Event location, what is happening. And at the same time we really cared that this reporter, stays anonymous for their own safety. We, privacy and security is utmost importance to us. So that's always our focus. So in that space, we de-identify them. We take out any information that could be identifiable, that could lead to their arrest, or could lead to someone identifying that it was them that reported. >> And how do you get this information to the people that are suffering this activity ground? How do they know about you, how do they know that you are anonymizing their information so there's not going to be repercussions if they report. You know, how do, kind of I guess your go-to-market, to steal a business terms, in making sure that people know this tool's available for help? >> It depends on the situation. For example in the conflict situation, we rolled it out, and we kept it low key for awhile. Because we didn't want government attacks, we didn't want people to be arrested, or to be tried. So we rolled it out. And it was word of mouth that spreads. And people started submitting supports. Actually the first project we did with conflict, we weren't sure if we were going to get one report, zero reports. The first week we got nothing. And then slowly as people learned about it they started submitting their reports. And we see our job as really elevating the otherwise marginalized voice. So you submit a report to us, we then take it. We verify it. We make it public. And that, we welcome, we encourage, we want people to consume it. Whether you're a student, whether you're a journalist, whether you're a government, whether you work in a nonprofit, the UN. It's been used to address human rights violations, it's been used to identify humanitarian hotspots. The data's phenomenal, and what you get from it. It's not just collecting data. We're not just about collecting the data. We want to make sure it's meaningful, and we want to derive insights. So we want to know what is the data actually telling us? >> Right, right. So just to be clear for people that don't know, so you're making that data available, you're cleansing the data, you're running some AI on it to try to get a bigger picture, and anyone with a login, any kind of journalist can now access that data in support of whatever issue or topic or story they're chasing? >> That's it Jeff. >> That's phenomenal. And just kind of size and scope. You've been at this I think you said since 2011. You know kind of how many active, activities, crisis, I don't know, what the definition is of a bucket of these problems. Are you tracking historically at a given point in time? Give us some kind of basic sizing type of dimensions. >> It really ranges, because it could, when we were tracking conflict for example, we were really focused on one area, and the surrounding countries. Because you had refugee population, you had displacement, you had all sorts of issues. But it could be anywhere from five projects, it just depends. And we want to make sure that each project we're taking on we're giving it our full attention, full scope. And I like to run the organization like a two-team pizza team. And so I don't take on more than I could handle. >> Right, right. So then how did it morph from the conflict to the Global Sustainability Goal? So we've worked with Western Digital, they're doing a lot of work, ASP's doing a lot of work on kind of these global sustainability goals. How did you get involved in that, and how did the two kind of dovetail together? >> So the elasticity of the cloud has helped our operation scale tremendously. And in 2016 we were selected as a top 10 global innovation, that could be applied to the Sustainable Development Goals, and-- >> So they found you, the UN find you, or did you get nominated? How did that happen? >> We were nominated, and from over 1,000 solutions we were chosen. >> Congratulations. >> Thank you. And we were showcased at the Solutions Summit which is hosted at the United Nations. And just based on that experience of meeting people that were doing really cool things in their respective communities, we launched the Global Action Mosaic. Because we wanted to create one place where people that are doing projects in their communities could submit it, and have it showcased. And the goals are not only to crowdsource the SGD's, but to also be a part of the effort to track what's happening. Who's doing what where, make it easy for people to search say, Jeff you decided to get involved in a project with education. You can go onto our Global Action Mosaic, search projects on education in your community or in other parts of the world and then get involved in it. So it's really creating a centralized place where people can get information on the global goals. >> Awesome. So that's pretty much the Global Action Mosaic. It's pretty much focused on the UN global goals versus your core efforts around the Humanitarian Tracker. >> Yes. >> That's great. So we're here at AWS. Have you always been on AWS? Is this something new? How does being on kind of the AWS infrastructure help you do your mission better? >> We are, we've been partners in running AWS since we actually started. >> Since the beginning. >> Yes we have Yusheheedi as one of our partners, development partners, AWS. And because one of the core, one of the most important things to us is privacy and security, we want to make sure that whatever data is being handled and received is stored securely. >> Right, right. >> And that information transmitted, handled is also being done so in a secure way. Like I mentioned, the elasticity of the cloud has helped us scale our mission tremendously. It's affordable, we've been able to us it, we've learned their machine-learning stock to de-identify some of the data that comes in. So we're firm believers that AWS is essential to how we run our operation. >> Because do the individual conflicts kind of grow and shrink over time? Do you see it's really a collection of kind of firing up hotspots and then turning down versus one long, sustained, relatively flat, from kind of a utilization and capacity point of view? >> Yeah, no it definitely, it flares up and you'll have like a year, months, weeks sometimes where it's just focused on one area. But one of the things we focus on, it's not just. So what is the data actually telling us? So say you're focusing on point A. But just down the street in location B there is a dire humanitarian emergency that needs to be addressed. The crowdsourced reports, combined with the data mining and the AI, helps us identify those hotspots. So everybody could be focused here, but there could be an emergency down the street that needs to be addressed as well. It just depends. >> And do you have your own data scientists or do you, do other people take your data and run it through their own processes to try to find some of these insights? >> We have both. >> You have both. >> Yeah. >> So what's been the biggest surprise when you anonymize and aggregate the data around some of these hotspots? Is there a particular pattern that you see over and over? Is there some insight, that now that you've seen so much of it, from kind of the (muffled speaking) that you can share and reflect on? >> I think it' very unique to each project to do. But there is one thing that I strongly support, that I don't see enough of, and that's the sharing of data within the organizations. And so, for example just getting to that culture where sharing your data between organizations is encouraged and actually done. Could help create a, create a pool of knowledge. So, for example we worked with 13 different organizations that were all tackling humanitarian events. The same one, in Syria. And the 13 did not share data and did not talk to each other. And so we found that for example, they were all focused on one area. When just a few miles down, there was a need that wasn't being addressed. But because they don't share information, they had no idea. >> Right. >> It was only when we were able to take a look at it, kind of from the, from an overarching view, looking all their data, we were able to say you know, it would be helpful, it would actually, you could save on resources, and less time, and less effort, and you guys are tackling a small funding pool to begin with. If you shared information and tackled different things, instead of focusing on one area, because you don't know what the other guys doing. >> And were they using crowdsource data, is there source data, or were they just trying to collect their own from the field? >> They were collecting their own. >> So I assume that the depth, and the richness, and the broadness of data is nothing like you're collecting. >> Well you get a different kind of, you get different kind of information when the individuals actually telling you what's happening versus you asking a very direct question like, "Are you healthy? Yes or No?". Whereas you give them the chance, they might tell you that they haven't eaten, and their diabetic and you know, give you other pieces of information. Where they're living, are they refugees? Are they healthy? Are they not healthy? Do they go to school? Do their kids go to school? How many kids they have? Are they a female-run household? All this information could help guide development in the proper way. >> Right, right. All right. So give you the final word, how should people get involved if they want to help? >> You can go to humanitariantracker.org if you want to volunteer with us. And if you're doing a project that is related to the UN's Sustainable Development Goals, I would like you to go to globalactionmosaic.org, and map it there, and be part of our community. >> So Hend, thank you for taking a few minutes to share your story, and for all the good work that you're doing out there. >> Thank you Jeff it was a pleasure. >> All right, she's Hend, I'm Jeff, you're watching theCUBE, we're at AWS Imagine nonprofit. Thanks for watching we'll see you next time. (techno music)