>>from around the globe. It's >>the Cube 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 Furrow, your host of the Cube with two great guests here. Travis Department director of analytics and Weather at Max. Our technologies and VJ teleplay Gotta Who's the chief? Modeling and data a simulation branch at Noah. Tell us about the success of this. What's the big deal? Take us through the award and why Max are what you guys do. >>Yeah, so Macs are is an organization. Does a lot of different activities unearth intelligence as well as space? We have about 4000 employees around the world. One side of the economy works on space infrastructure, actually building satellites on all the infrastructure that's going to help us get us back to the moon and things like that. And then on the other side we have a north of intelligence group, which is where, I said, and we leverage remote sensing information for science information to help people better understand how, how and what they do might impact the Earth or have the earth, and it's activities might impact their business mission. Our operation. 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. Ah, so we we knew? No. I had capabilities running America weather prediction models and very traditional on Prem. Big, beefy ah, high performance compute supercomputers. But we wanted to do it in The cloud we want to do is AWS is a key part. So we collaborated with B. J and Noah and his team is there to help pull that off. They gave this access public domain information, but they showed us the right places to look. We've had some of the research scientists talking, and after 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. I'm we got pretty excited. Once we saw some of the outcome >>Travis to be, Jay was just mentioning the relationship. Can you talk about the relationship together because this is not your classic Amazon partner client relationship that you have. You guys have been partnering together V. J and your team with AWS. Talk about the relationship and that and how Amazon plays because it's a unique partnership plane in more detail at specific relationship. >>Yeah, with Max or in AWS. You know, our partnership has gone back A number of years on Macs are being a fairly large organization. There's lots of different activities. I think Max Star was the first client of 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 and archive that just moving across the Internet would probably still be going. Um, so the snowmobile is 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, you know, the scalable Ai ml were able to scale out that architecture scale out that compute the much easier, dynamic and really cost effective way with AWS, because when we don't need to use the machines, we turn them off. We don't have a big data center sitting somewhere. We have to have security, have all the overhead costs of just keeping the lights on. Literally. AWS allows us to run our organization and a much more efficient way. Um and Noah, you know, they're 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 computer, things like that. And I think a lot of the stuff that we've done here, Max our with our HPC HPC solution in the cloud. It's something that's pretty interesting to know, and it's 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 was probably the the short answer, but it all started with our people. Uh, you know, we have some really strong engineers, really strong data scientists that fundamentally have a background in meteorology or atmospheric science, you know? So they understand the physics. So you know why the wind blows is the way it doesn't. Why Cloud's doing clouds to do, Um, but we also having a key strategic partnership with AWS. We really have to tap into some of their subject matter experts. And we really put those people together, you know, and come up with new solutions, new innovative ideas, stuff that people hadn't tried before. We're able to steer a little bit of AWS is product roadmap for is 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 that's what allowed us to move pretty quick fashion. Um, you know, it's it's neat stuff technology, but it really comes down to the people. Um, and I feel very honored and privileged to work with both great people here. Attacks are as well as aws, um, as well as being able to collaborate with your great teams. That power, it's been a lot of fun. Well, >>Travis gonna create example? I think it's a template that could be applied to many other areas, certainly even beyond. You've 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 the feeling? Give us a quick side from the field? >>Yeah. I mean, I don't know if there's really a lot of good words that kind of sum it up. It's Ah, I shared the news with the team last night, and you know, there are a lot of a lot of good responses that came from a lot of people think it's cool. And at the end of the day, a lot of people on our team, you know, took a hobby or a passion of weather and turned it into a career. Ah, and being acknowledged and recognized by groups like AWS for best solution in a particular thing. Um, I think we take a lot of that to heart. And, ah, we're very honored and proud of what we were able to do and proud that other people recognize the need stuff that we're doing well, >>Certainly taking advantage. The cloud, which is large scale. But you 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 in a lot of impact to get it right. So congratulations on ECs. >>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. Good to be here. >>So Noah, National Oceanic Atmospheric Administration, National Weather Center, National Center for Environmental Predictions, Environmental Modeling Center year. 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 forecast to save lives and property and improve the economy of the nation. And that's part of that. That the national weather services responsible for providing data and also the forecasts to the public and the industry and be responsible for providing the guidance on how they create the forecasts. So we are at the Environmental Modeling Center, uh, the nation's finest institute in advancing our numerical weather prediction modelling development, and you play it off 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. That's that's the kind of a range of products that we don't lock and provide are our key for managing the emergency services and patch it management and mitigation and also improving the nation's economy by preparing well in advance for the future events. And it's it's a science based organization, and we have ah well class scientists working in this organization. I manage about 170 of them at the moment of modeling center. They're all PhDs from various disciplines, mostly from meteorology, atmospheric sciences, oceanography, land surface modelling space weather, all weather related areas and the mathematics and computer science. And we are at the stage where we are probably the most. Uh huh. Most developed, uh, advanced modelling center that we use almost all possible computational resources available in the world. So this is a really computational in terms of user data, user computer seems off. Uh, 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 the services every hour. For some sense is like the CDO rather our rates for every three hours for hurricanes and for every six hours for the regular, Rather like the participation, uh, the temperature forecast. So all the data that you see coming out from either the public media, our department agencies, they are originated in our center and disseminated in various forms. I think no one is the only center in the world that provides all this information for your past. So it is, ah, public service organization and we riding on a visa with society. >>We'll I love your title, Chief modeling and data, a simulation title branch of a lot of these organizations. This >>is >>whether it's ever critical. I want to get your thoughts cause we were talking before we came on about how the Hurricane Katrina was something that really kind of forcing you to rethink things. Whether it is an evolving system, it's always changing. Either the catastrophe or something happens. Were you trying to 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 big job. It's a lot of data you need. Horsepower need computing. You need to stand up. Some HPC take us through like like the thinking around the organization. And what was The impact is that you see, because whether does have that impact. >>So traditionally, you know, as you mentioned, there are radius weather phenomenon that you describe like the five rather the Americans, every presentation, the flooding. So we developed solutions for individual weather phenomena, and, uh, 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 has to be changed. And then there is Another big problem is that there's 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, uh, development activity that we cannot take advantage. And they have no incentive 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 waas 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 in the massive cloud that is Amazon. How is that help to you? Can you take a minute to explain, but walk us through? >>What? >>Aws? There >>are a few example. Second site. But before then, I would like to really appreciate a Travis Hartman from Max. Are you know who is probably the only private sector partner that we had in the beginning. And now we're expanding on. That s so we were able to share our community. Cores with Max are and without how they were able to establish this and drive modeling system as it is done in operations that Noah and they were able to reproduce operational forecast using the cloud resources. And then they went ahead and did even more by scaling the modeling systems is that it can run even faster and quicker them are what insert no operations can do. So that gives us one example of how the cloud can be used. You know, the same forecast that we produce, ah, globally, which will take about eight minutes per day. And, uh, Max I was able to do it much faster, like 50% improvement and in the efficiency of the colors. And now the one piece of this is that the improvements that matter are other collaborators are using, or cords that they're putting into the system are coming back to us. So we take advantage of that, improving the efficiency in operations. So this is that this is like a win win situation for both, uh, who are participating in the R and D on 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 when you can run it more efficiently and you can create an ensemble of solutions that can be captured toe individual needs. And the one additional thing I want to mention about User Cloud is, is that you know, this is like when you have a need, you can search the compute you can. Instead she 8000 sub simulations to test a new innovation. For instance, you don't need to wait for the resources to be done in a sequential manner. Instead, you can ramp up the production off these apartments in no kind and without Don't worry about. Of course, the cost is the fact that we need to worry about, but otherwise the capacity is there. The facilities are reacting to take advantage of the cloud solutions. If I'm a >>computer scientist person, I'm working on a project. Now I have all this goodness in the cloud, how's morale been and what's the reaction been like from from people doing the work. Because usually the bottleneck has been like I gotta provision resource. I gotta send a procurement request for some servers or I want to really push some load. And right now, I got a critical juncture. I mean, it's got a push morale up a bit, and you talk about the impact to the psychology of the people in your organization. >>Um, I haven't. I have two answers to this question. One from a scientist perspective like me. You know, I was not a computer scientist from the beginning, but I became a software engineer, kind of because I have to work with these software and hardware stuff more more on solving the computational problems than the critical problems. So people like us who have invested their careers in improving the science, they were not care whether it's ah, uh hbc on premise Cloud, what will be delighted to have, uh, resources available alleviate that they can drive. But on the other hand, the computer computational engineers are software engineers who are entering into this field. I think they are probably the most excited because of these emerging opportunities. And so there is a kind of a friction between the scientific and the computational aspects off personnel, I would say. But that difference is slowly raising on and we are working together as never before. So the collective moral is very high to take advantage of these resources and opportunities. I think way of making the we're going in the right direction. >>It's so much faster. I mean, in the old days, you write a paper, you got to get some traction. Gonna do a pilot now It's like you run an experiment, get it out there. VJ I'm very impressed with the organization. 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 providing 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 waiting to innovate with community with large scale, multi scale data points. So congratulations and >>thank you. >>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 is part of AWS Public Sector Partner Awards program. I'm John Furrier. The best in show for HPC Solutions. China's Hartman Max, our technologies and Vijay tell Apartado at Noah. Two great guests. Thanks for watching. Yeah, Yeah, yeah, yeah, yeah, yeah

>>live from Atlanta, Georgia. It's the Q covering Answerable Fest 2019. Brought to you by Red Hat. >>Hey, welcome back, everyone. It's the cubes. Live coverage here in Atlanta, Georgia, for answerable fast. Part of redheads. Big news. Ansel Automation Platform was announced. Among other things, they're great products. I'm John for ear, with my coast to minimum, but two great guests. You unpack all the automation platform features and benefits. Walter Bentley, senior manager. Automation Practicing red hat and vj Job Olu, director of Red Hat Consulting Guys Thanks for coming on. Thanks. So the activity is high. The buzz this year seems to be at an inflection point as this category really aperture grows big time seeing automation, touching a lot of things. Standardization. We heard glue layer standard substrate. This is what answer is becoming so lots of service opportunity, lot of happy customers, a lot of customers taking it to the next level. And a lot of customers trying to consolidate figure out hadn't make answerable kind of a standard of other couples coming in. You guys on the front lines doing this. What's the buzz? What's the main store? What's the top story going on around the service is how to deploy this. What are you guys seeing? >>So I think what we're seeing now is customers. Reactor building automation. For a long time, I have been looking at it at a very tactical level, which is very department very focused on silo. Whether country realizes with this modern develops and the change in how they actually go to the market, they need to bring the different teams together. So they're actually looking at watching my enterprise automation strategy be how to actually take what I've learned in one organization. And I still roll it across the enterprise so that now struggling and figuring out how to be scared, what we have, how do we change the culture of the organization to collaborate a lot more and actually drive automation across enterprise? >>Walter One of the things we've been we've talked about all the time in the Cube, and it's become kind of cliche. Digital transformation. Okay, I heard that before, and three things people process, technology, process and capability you guys have done You mentioned the siloed having capabilities that's been there. Check was done very, very well as a product technology Red hat in the portfolio. Great synergies. We talked about rail integration, all the benefits there. But the interesting thing this year that I've noticed is the people side of the equation is interesting. The people are engaged, is changing their role because automation inherently changes there, function in the organization because it takes away probably the mundane tasks. This is a big part of the equation. You guys air hitting that mark. How do you How are you guys seeing that? How you accelerating that has that changing your job, >>right? So customers are now economy realizing that going after automation in a very tactical manner is not exactly getting them what they want as a far as a return on investment in the automation. And what they're realizing is that they need to do more. And they're coming to us and more of an enterprise architectural level and say we want to talk mortgage grander strategy. And what they're coming to realize is that having just one small team of people that were calling the Dev Ops team is not gonna be ableto drive that adoption across the organization. So what we're trying to do is work with customers to show them how they collaboration in the culture of peace is huge. It's a huge part of adopting automation. Answerable is no longer considered a emerging tech anymore. And and I when I say that, I mean a lot of organizations are using answerable in many different ways. They're past that point, and now they're moving on to the next part, which is what is our holistic strategy and how we're gonna approach automation. And And we wanted leverage danceable, unanswerable tower to do that. >>Does that change how you guys do your roll out your practices in some of your programs? >>Well, we did have to make some adjustments in the sense of recognizing that the cultural piece is a pivotal part of it, and we can go in and we can write playbooks and rolls, and we can do all those things really great. But now we need to go in and help them structure themselves in a way where they can foster that collaboration and keep a moment. >>And I'll actually add on to that so reactive, large, open innovation labs three years ago, and what we have to learn doing that is using labs and allows practices to actually help customers embrace new culture and change. How they actually operate has actually helped us take those practices and bring it into our programs and kind of drive that to our customers. So we actually run our automation adoption program and the journey for customers through those practices that we actually learned in open innovation loves like open practice, library, even storming priority sliders and all of those modern techniques. So the goal is to help our customers understand those practices and actually embrace them and bring them into the organization to drive the change that that's looking for within the organization. >>A. J. Is there anything particular for those adoption practices when you're talking about Cloud? Because the communication amongst teams silos, you know, making things simpler is something that we absolutely do need for cloud. So I'm just curious how you connect kind of the cloud journey with the automation journey. >>So all of the journey program that actually created, whether it's a contender adoption program or the automation adoption program, we actually followed the same practices. So whether you're actually focused on a specific automation to, like, answerable or actually embarking on hybrid multicolored journey. We actually use the same practices so the customers don't have toe learn new things every time you have to go from one product, one of the so that actually brings a consistent experience to customers in driving change within the organization. So let's picture whether it is focusing automation focused on cloud migrating to the cloud. The practices remained the same, and the focus is about not trying to boil the ocean on day one. Try to break it into manageable chunks that give it a gun back to the business quickly learned from the mistakes that you make in each of the way and actually build upon it and actually be successful. >>So, Walter, I always love when we get to talk to the people that are working straight with customers because you come here to the conference, it's like, Oh, it's really easy Get started. It doesn't matter what role or what team you're in. Everybody could be part of it. But when you get to the actual customers, they're stumbling blocks. You know what are some of those things? What are some of the key things that stop people from taking advantage of all the wonderful things that all the users here are doing >>well. One of the things that I've identified and we've identified as a team is a lot of organizations always want to blow the ocean. And when and when it comes down to automation, they feel that if they are not doing this grand transformation and doing this this huge project, then they're not doing automation. And the reality is is that we're Trent with showing them that you can break things up into smaller chunks, as Visi alluded to. And even if you fail, you fail fast and you can start over again because you're dealing with things in a smaller chunk. And we've also noticed that by doing that, we're able to show them to return on investment faster so they can show their leadership, and their leadership can stand behind that and want to doom. Or so that's one of the areas. And then I kind of alluded to the other area, which is you have to have everybody involved. You want just subject matter experts riding content to do the automation. You don't want that just being one silo team. You want to have everybody involved and collaborate as much as possible. >>Maybe can you give us an example? Is about the r A y How fast to people get the results and, you know, prove toe scale this out. >>So with the automation adoption journey, what we're able to do is is that we come in and sit down with our customers and walk them through how to properly document their use cases. What the dependencies, What integration points, possibly even determining what is that? All right, ranking for that use case. And then we move them very quickly in the next increment. And in the next increment, we actually step them through, taking those use cases, breaking them down into minimum viable products and then actually putting those in place. So within a 90 day or maybe a little bit more than a little bit more than the 90 day window, were able to show the customer in many different parts of the organization how they're able to take advantage of automation and how the return on investment with hopes of obviously reducing either man hours or being able to handle something that is no a mundane task that you had to do manually over and over again. >>What are some of the things that people get confused about when they look at the breath of what's going on with the automation platform? When I see tool to platform, transitions are natural. We've seen that many times in the industry that you guys have had product success, got great community, that customers, they're active. And now you've got an ecosystem developing so kind of things air popping on all cylinders here. >>So the biggest challenge that we're actually being seeing customers is they actually now come to realize that it's very difficult to change the culture of the organization right there, actually embarking on this journey and the biggest confusion that is, how do we actually go make those changes? How do we bring some of the open practice some of the open source collaboration that Riddle had into the organization so they actually can operate in a more open source, collaborative way, and what we have actually learned is we actually have what we call its communities of practice within Red Hack. It is actually community off consultants, engineers and business owners. The actual collaborate and work together on offering the solutions to the market. So we're taking those experiences back to our customers and enabling them to create those communities of practice and automation community that everybody can be a part off. They can share experiences and actually learn from each other much easier than kind of being a fly on the wall or kind of throwing something or defense to see what sticks and what does not. >>What's interesting about the boiling the ocean comment you mentioned Walter and B J is your point. There is, is that the boil? The ocean is very aspirational. We need change rights. That's more of the thing outcome that they're looking for. But to get there is really about taking those first steps, and the folks on the front lines have you their applications. They're trying to solve or manage. Getting those winds is key. So one of things that I'm interested in is the analytics piece showing the victory so in the winds early is super important because that kind of shows the road map of what the outcome may look like versus the throw the kitchen, sink at it and, you know, boil the ocean of which we know to the failed strategy. Take us through those analytics. What are some of the things that people tend to knock down first? What are some of the analytical points that people look at for KP eyes? Can you share some insight into that? >>Sure, sure. So we always encourage our customers to go after the platform first. And I know that may sound the obvious, but the platform is something that is pretty straightforward. Every organization has it. Every organization struggles with provisioning, whether of a private cloud, public cloud, virtualization, you name it. So we have the customer kind of go after the platform first and look at some of their day to operations. And we're finding that that's where the heaviest return on investment really sits. And then once you get past that, we can start looking like in the end, work flows. You know, can they tie service now to tower, to be able to make a complete work flow of someone that's maybe requesting a BM, and they can actually go through that whole workflow by by leveraging tower and integration point like service. Now those air where we're finding that the operators of these systems going getting the fastest benefit. And it also, of course, benefits the business at the end of the day because they get what they need a lot fast. >>It's like a best practice and for you guys, you've seen that? Yes, sir. Docked with that out of E. J. What's your comment on all this? >>So going back to the question on metrics Automation is great, but it does not provide anybody to the business under the actually show. What was the impact, whether it's from a people standpoint, cost standpoint or anything else. So what we try to drive is enable customers. You can't build the baseline off where they are today, and as they're going through the incremental journey towards automation, measure the success of that automation against the baseline. And that actually adds the other way back to the customer. As a business you didn't get to see. I was creating a storage land. I was doing it probably 15 times a month. Take it or really even automated. It spend like a day created a playbook. I'll save myself probably half, of course, and that could be doing something that's better. So building those metrics and with the automation analytics that actually came in the platform trying those bass lines. So the number of executions, actually the huge value they'll actually be ableto realize the benefits of automation and measure the success off within enterprise. >>So I'm a customer prospect, like I want to get a win. I don't want to get fired. I won't get promoted. Right, I say, Okay, I gotta get a baseline and knock down some playbooks. Knock that down first. That what you're gonna getting it. That's a good starting. >>Starting. Understand your baseline today. Plan your backlog as to what you want to knock down. And once you know them down, build a dashboard as to what the benefits were, what the impact was actually built upon it. You actually will see an incremental growth in your success with automation. >>And then you go to the workflow and too, and that's your selling point for the next level. Absolutely good playbook. Is that the automation programs that in a nutshell or is that more of a best practice >>those components of the ah, the automation adoption journey that we allow the customer to kind of decide how they want their journey to be crafted. Of course, we have a very specific way of going about and walking them through it. But we allowed in the kind of crap that journey and that is those the two components that make up the automation. >>We're gonna put you guys on the spot with the tough question We heard from G. P. Morgan yesterday on the Kino, which I thought was very compelling. You know, days, hours, two minutes. All this is great stuff. It's real impact. Other customers validate that. So, congratulations. Can you guys share any anecdotal stories? You know, the name customers? Just about situations Where customs gone from this to this old way, new way and throw some numbers around Shearson Samantha >>is not a public reference, but I like to give you a customer. Exactly. Retail company. When we first actually went and ran a discovery session, it took them 72 days to approach in an instance. And the whole point was not because it took that long. It because every task haven't s l. A We're actually wait for the Acela manually. Go do that. We actually went in >>with our 72 hours, two days, two days, >>actually, going with the automation? We Actually, it was everybody was working on the S L. A. We actually brought it down to less than a day. So you just gave the developers looking to code 71 days back for him to start writing code. So that's the impact that we see automation bringing back to the customers, right? And you'll probably find the use causes across everywhere. Whether J. P. Morgan Chase you actually had the British Army and everyone here on states talking about it. It is powerful, but it is powerful relief you can measure and learn from it >>as the baseline point. Get some other examples because that's that's, uh, that's 70 days is that mostly delay its bureaucracy. It's It's so much time. >>It's manual past and many of the manual tasks that actually waiting for a person to do the task >>waterfall past things sound, although any examples you can >>yes, so the one example that always stands out to me and again, it's a pretty interviewing straight forward. Is Citrix patching? So we work with the organization. They were energy company, and they wanted to automate patching their searches environment, patching this citrus environment took six weekends and it took at least five or six engineers. And we're talking about in bringing an application owners, the folks who are handling the bare metal, all all that whole window. And by automating most of the patching process, we were able to bring it down to one weekend in one engineer who could do it from home and basically monitor the process instead of having to be interactive and active with it. And to me, that that was a huge win. Even though it's, you know, it's such dispatching. >>That's the marketing plan. Get your weekends back. Absolutely awesome. Shrimp on the barbecue, You know, Absolutely great job, guys. Thanks for the insight. Thanks. Come on. The key. Really appreciate it. Congratulations. Thank you. Thanks for sharing this queue here. Live coverage. Danceable fest. Where the big news is the ass. Full automation platform. Breaking it down here on the Q. I'm John. First to Minutemen. We're back with more coverage after this short break