 From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards. Brought to you by Amazon Web Services. Everyone, welcome to this CUBE coverage of AWS Public Sector Partner Awards program. I'm John Furrier, your host of theCUBE. We've got two great guests here, Travis Hartman, director of analytics and weather at Maxar Technologies and Vijay Talapragada, who's the chief modeling and data assimilation branch at NOAA. Tell us about the success of this. What's the big deal? Take us through the award and why Maxar, what do you guys do? Yeah, so Maxar is an organization that does a lot of different activities in earth intelligence as well as space. We have about 4,000 employees around the world. One side of the company works on space infrastructure actually building satellites and all the infrastructure that's gonna help us get us back to the moon and things like that. And then on the other side, we have an earth intelligence group, which is where I sit and we leverage remote sensing information, earth science information to help people better understand how and what they do might impact the earth or how the earth and its activities might impact their business mission or operations. So what we wanted to set out to do was help people better understand how weather could impact their mission business or operations. And a big element of that was doing it with speed. So we knew NOAA had capabilities of running numerical weather prediction models and very traditional on-prem, big, beefy, high-performance computers, supercomputers. But we wanted to do it in the cloud. We wanted to use AWS as a key partner. So we collaborated with VJ and NOAA and his teams there to help pull that off. They gave us access public domain information, but they showed us the right places to look. We've had some of our research scientists talking and after a pretty short effort, it didn't take a lot of time. We were able to pull something off that a lot of people didn't think was possible. We got pretty excited once we saw some of the outcomes. Travis, VJ was just mentioning the relationship. Can you talk about the relationship together? Because this is not your classic Amazon partner, the client relationship that you have. You guys have been partnering together, VJ and your team with AWS. Talk about the relationship and how Amazon play with it because it's a unique partnership. Explain in more detail that specific relationship. Yeah, with Maxar and AWS, our partnership has gone back a number of years. And Maxar being a fairly large organization, there's lots of different activities. I think Maxar was the first client of the AWS Snowmobile, where they have the big tractor trailer back up to a data center, load all the data in, and then take it to an AWS data center. We were the first users of that because we had over 100 petabytes of satellite imagery in an archive that just moving across the internet and probably still be going. So the Snowmobile was a good success story for us, but just with the amount of data that we have, the amount of data we collect every day and all the analytics that we're running on it, whether it's in an HPC environment or the scalable AI ML, we're able to scale out that architecture, scale out that compute in a much easier dynamic and really cost effective way with AWS. Cause when we don't need to use the machines, we turn them off. We don't have a big data center sitting somewhere where we have to have security, have all the overhead costs of just keeping the lights on literally. AWS allows us to run our organization in a much more efficient way. And NOAA, they're seeing some of that same success story that we're seeing as far as how they can use the cloud for accelerating research, accelerating how the advancement of numerical weather prediction from the United States can benefit from cloud, from cloud architecture, cloud computing, things like that. And I think a lot of the stuff that we've done here with Maxar with our HPC solution in the cloud is something that's pretty interesting to know. And it's a good opportunity for us to continue our collaboration. If I could drill down on that solution, architecture for a minute, how did you guys set up the services and what lessons did you learn from that process? We're still learning, it's probably the short answer, but it all started with our people. We have some really strong engineers, really strong data scientists that fundamentally have a background in meteorology or atmospheric science. So they understand the physics of why the wind blows the way it does and why clouds do what clouds do. But we also, having a key strategic partnership with AWS, we were able to tap into some of their subject matter experts and really put those people together and come up with new solutions, new innovative ideas, stuff that people hadn't tried before. We were able to steer a little bit of AWS's product roadmap as far as what we were trying to do and how their current technology might not have been able to support it, but by interacting with us, gave them some ideas as far as what the tech had to move towards. And then that's what allowed us to move in a pretty quick fashion. It's neat stuff technology, but it really comes down to the people. And I feel very honored and privileged to work with both great people here at MacShar, as well as AWS, as well as being able to collaborate with the great teams at that one. It's been a lot of fun. Well, Travis, got a great example. And I think it's a template that can be applied to many other areas, certainly even beyond. You got large scale, multi-scale situation there. Congratulations. Final question, what does it mean to be an award winner for AWS Partner Awards? As part of the show, you're the best in show for HPC. What's it like? What's your feeling? Give us a quick story from the field. Yeah. I mean, I don't know if there's really a lot of good words that can kind of sum it up. I shared the news with the team last night and there were a lot of good responses that came from it. A lot of people think it's cool. And at the end of the day, a lot of people in our team took a hobby or a passion of weather and turned it into a career. And being acknowledged and recognized by groups like AWS for best solution in a particular thing. I think we take a lot of that to heart and we're very honored and proud of what we were able to do and proud that other people recognize the neat stuff that we're doing. Well, certainly taking advantage of cloud, which is large scale, but you're on a great wave. You've got a great area. I mean, whether you talk about whether it's exciting, it's dynamic, it's always changing, it's big data, it's large scale. So you get a lot of problems to solve and a lot of impact too, when you get it right. So congratulations on an excellent- Thank you very much. Great mission. Thank you. Love what you do. Love to follow up again. Maybe do another interview and talk about the impact of weather and all the HPC kind of down the road. But Travis, thank you very much. Thank you, appreciate it. Good to see you. Thank you, great to be here. So NOAA National Oceanic Atmospheric Administration, National Weather Center, National Center for Environmental Predictions, Environmental Modeling Center, that's your organization. You guys are competing to be best in the world. Tell us what you guys do at a high level, then we'll jump into some of the successes. So the National Weather Service is responsible for providing weather forecasts to save lives and property and improve the economy of the nation. And as part of that, the National Weather Service is responsible for providing data and also the forecasts to the public and to the industry. And we are responsible for providing the guidance on how they create the forecasts. So we are at the Environmental Modeling Center, the nation's finest institute in advancing our numerical weather prediction modeling, development and utilization of all the data that's available from the world to initialize our models and provide the future state of the atmosphere from hours all the way to seasons and years. And that's the kind of a range of products that we develop and provide are key for managing the emergency services and hazard management and mitigation and also improving the nation's economy by preparing well in advance for the future events. And it's a science-based organization and we have world-class scientists working in this organization. I manage about 170 of them at Environmental Modeling Center. They're all PhDs from various disciplines, mostly from meteorology, atmospheric sciences, oceanography, land surface modeling, space weather, all weather related areas and the mathematics and computer science. And we are at the stage where we are probably the most most developed advanced modeling center that we use almost all possible computational resources available in the world. So this is a heavily computational in terms of use of data, use of computers, use of all the power that we can get. And we have a 3.5 petaflop machine that we use to provide these weather forecasts. And they provide these services every hour for some instances like the severe weather outbreaks and for every three hours for hurricanes and for every six hours for the regular weather, like the precipitation, the temperature forecast. So all the data that you see coming out from either the public media or the government agencies, they all are originated in our center and disseminated in various forms. And I think NOAA is the only center in the world that provides all this information for your past. So it is a public service organization and we pride in our service to the society. Well, I love your title, Chief Modeling and Data Assimilation title, branch of all these organizations. This is weather is critical. I want to get your thoughts because we were talking before we came on about how the hurricane in Katrina was something that really kind of forced everyone to rethink things. Weather is an evolving system. It's always changing, either there's a catastrophe or something happens or you're trying to be proactive predicting, say, whether it's a fire season in California, all kinds of things going on that's not, it's always hard to get a certain prediction. You have a big job, it's a lot of data. You need horsepower, you need computing. You need to stand up some HPC. Take us through like the thinking around the organization because, and what's the impact is that you see because weather does have that impact. So traditionally, you know, as you mentioned, there are various weather phenomena that you described, like the fire weather, the hurricanes, the heavy precipitation, the flooding. So we developed solutions for individual weather phenomena and we have grown in that direction by developing separate solutions for separate problems. And very soon it became obvious that we cannot manage all these independent modeling systems to provide the best possible forecasts. So the thinking had to be changed. And then there is another bigger problem is that there is a lot of research going out in the community, like the academic institutes, the universities, other government labs. There are several people working in these areas and all their work is not necessarily a coordinated development activity that we cannot take advantage and there are no incentives for people to come and contribute towards the mission that we are engaged in. So that actually prompted to change the direction of thinking. And as you mentioned, Hurricane Katrina was an eye opener. We had the best forecasts, but the dissemination of that information was not probably accurate enough. And also there is a lot of room for improvement in predicting these catastrophic events. How are you guys using AWS? Because HPC, high performance computing, I mean, you can't ask for more resources than the massive cloud that is Amazon. How has that helped you? Can you take a minute to explain how to walk us through the AWS internship? There are a few examples I can cite, but before then I would like to really appreciate Travis Hartman from Maxar, who is probably the only private sector partner that we had in the beginning. And now we are expanding on that. So we were able to share our community codes with Maxar. And with our help, they were able to establish this entire modeling system as it is done in operations at NOAA. And they were able to reproduce our operational podcast using the cloud resources. And then they went ahead and did even more by scaling the modeling systems so that it can run even faster and quicker than what NOAA operations can do. So that gives you one example of how the cloud can be used. The same forecast that we produce globally, which will take about eight minutes per day. And Maxar was able to do it much faster, like 50% improvement in the efficiency of the codes. And now the advantage of this is that the improvements that Maxar or other collaborators who are using our codes that they are putting in into the system are coming back to us. So we take advantage of that in improving the efficiency in operations. So this is like a win-win situation for both who are participating in the R&D and who are using it in operations. And on top of it, you can create multiple configurations of this model in various instances on the cloud and you can run it more efficiently and you can create an ensemble of solutions that can be catered to individual needs. And the one additional thing I wanted to mention about use of cloud is that this is like, when you have a need, you can search the compute. You can instantiate thousands of simulations to test a new innovation, for instance. You don't need to wait for the resources to be done in sequential manner. Instead, you can ramp up the production of these experiments in no time. And without worrying about, of course, the cost is the factor that we need to worry about. But otherwise the capacity is there, the facilities are there to take advantage of the cloud solutions. Well, Vijay, I'm very impressed with your organization. I'd love to do a follow-up with you. I love the impact that you're doing, certainly in the weather impact society from forecasting disasters and giving people the ability to look at supply chain, whether it's planning for potentially a fire season or water shortage or anything going on there. But also it's a template. You're exceeding a new kind of way to innovate with community, with large-scale, multi-scale data points. So congratulations and thank you very much. I'm John Furrier here, part of AWS partner awards program, best HPC solution, great, great example, great use case, great conversation. Thanks for watching. Two great interviews here as part of AWS public sector, partner awards program. I'm John Furrier. The best in show for HPC solutions, Travis Hartman, Maxar Technologies and Vijay Talapargada at NOAA. Two great guests. Thanks for watching.