AWS re Invent 2020 Advancing the future of space in the cloud

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hello everybody my name is shane hawthorne and i'd like to welcome you to reinvent 2020 and our session where we're going to be discussing advancing the future of space in the cloud as i said my name is shane hawthorne and i've been here at aws for about three and a half years and have 30 years of experience in the space industry before i came to aws i started at aws by building the aws ground station and i am now the space technology leader for one of aws's newest organizations the aerospace and satellite solutions division and i'm working in that organization with a lot of great customers like maxar so today i'm joined by dr walter scott the executive vice president and cto of maxar technologies and we're going to be jumping in and talking to you guys about how aws has been supporting and providing services and cloud capability to maxar to help them advance the future of space in the cloud we're going to do that by first off providing an introduction into the aerospace's satellite solutions division where i'll talk to you about what we've learned and how come we started this new organization to help our aws space customers and then we're going to segue over to a great presentation by dr scott where he's going to talk about how maxar truly is applying the cloud in space he's going to do that by talking to you about some technologies that maxar has been using in order to help their satellites image the world and do better things for the world taking care of different types of natural disasters taking care of helping people figure out how to respond to covid and then we're going to expand out into how maxar is actually supporting uh interplanetary exploration how they're helping the world to start moving towards colonizing and working around the moon and then finally talking about how maxar does a number of incredible things working with the weather so what are we doing with aws aerospace's satellite solutions aws as everybody knows provides secure flexible scalable and cost-efficient cloud solutions to help our commercial and our public sector customers build satellites conduct space operations conduct launch operations with rockets and then re-imagine how space exploration can be done in the future and we're doing that in building for a key reason that is mainly that aws has the most experience in cloud we've been building enterprise systems on the cloud since 2006 and our space customers need that level of experience to help them expand into earth orbit to the moon and then later we also provide the most functionality of any of the cloud services to support space with more than 175 services in order to provide support to space workloads on the earth and in orbit around the earth and then someday even out to the moon we're able to give that functionality and help people build the space enterprises that they need using cloud services microservices and products we have industry-leading artificial intelligence and machine learning which allows you to work both on the earth's surface in the cloud and up in space to apply machine learning and artificial intelligence to some incredible workloads that can help you identify buildings they can help you figure out behaviors and infer decisions from the data collected on the satellite so that you could tip and cue satellites on orbit or do the same types of operations down on the ground and when you're getting that data down to the ground you want to get that data down to the ground quickly into a large network around the world that's where aws ground station as a service comes in it allows you to get your space data faster you can downlink that data to aws get it through our ground station as a service and into the cloud quickly so that you can start using these services and products to help process your data help store it and distribute it to your customers around the world and then if you need support if you want to build things at a greater scale we have the largest community of partners available so that you can access thousands of systems integrators and independent software vendors or isvs as we call them to help you build new things in space and continue growing the world's efforts to grow into space to the moon and beyond and why do we do that we do that because even in space customers want to service experience and that's what aws delivers it delivers you first of all security we have a resilient global network of data centers composed into our aws regions and availability zones to provide you unrivaled redundancy processing and velocity for your data around the world and in processing it then we provide you the elasticity that you need to be able to scale your services by the minute that means that based on different use cases and workflows that you might be working on you're actually able to scale out when you need to get all the extra capacity that you need the storage the ability to move your data and then scale back in when you don't need that service and that allows you to be efficient and save your capex for different uses other than building ground station networks or building your own ground operations and then you're taking advantage of aws's worldwide network to provide unrivaled low-latency access to your data if you're using ground station as a service and then moving the data that you you receive at the aws ground station service around our network you can actually get data at any of our ground stations around the world to your virtual private cloud in hundreds of milliseconds that allows you to get your data where you want it and when you need it in near real time and that gives you immediate fulfillment so that your customers are able to get the data and the decisions and the inferences that you're providing them or you're able to get your data to them at the velocity that they need so let me give you an example of where that scaling out and scaling in and that access to aws services can really enable the space service experience let me show you this picture of the southern part of the united states as you all will well know we've been watching the southern united states for a number of weather events hurricanes and other issues that we need to be careful of because we want to protect people and we want to warn them when there's issues that they have to be aware of so in a typical day we have a low weather or no weather environment the cloud is able to allow our customers to really probably just move along at a very low rate there may be doing some level of dynamic analysis some level of prediction but overall it's a quiet day there's not a lot of work going on so there's a low amount of compute being used and a low amount of storage but let's say that a weather event does start to move in now things start to spool up first responders and emergency reaction people state governments national government fema everybody needs to start weathering monitoring this weather and start getting ready to weather the event and now your processing starts to spool up you're starting to collect data you're sparting starting to distribute data through content delivery networks you're starting to see people querying and getting information and then putting information back into the cloud to enable them to coordinate responses and start to do work this is where the cloud comes in to be so valuable as you spool up and you need more and more services and more and more capacity more and more storage you have the ability to do that and you're able to use that information to benefit people to alert people and help warn people and then when you go back to that previous quiescent state where you don't have much going on you can spool down all of those servers all the ec2 instances you can start to decrease your s3 storage that you're using to monitor that event and pretty soon you get back to normal and you're not paying for any of the services that you needed during that big active event because they're simply not needed at that time that's the type of power that we're able to provide to our aws customers and so i wanted to give you that example and then once again welcome dr walter scott to present his discussion about how maxar technologies is applying the cloud in space over to you walter thanks shane maxxr is a company that's behind many of the things that we depend on whether it's satellite imagery that we see on our mobile phones or creates the maps that we use to go from place to place the 3d models that are used for placement of cellular infrastructure or satellites that deliver satellite radio satellite tv satellite internet or even things that go to other planets i want to talk about one of the first ways first examples of how maxar and aws are working together hurricane laura was a devastating windstorm that went through the southern united states this past summer and what maxar does in response to any disaster of this type is start with our massive library of up-to-date satellite imagery about 100 petabytes that's stored in aws we pulled that imagery from glacier and s3 and used that as part of something that we call the digital globe which is a living digital twin of the surface of the earth it consists of the imagery and a variety of other information layers many of which we extract from the imagery and the way that we extract that those data layers from the imagery is using something that we call deepcore that runs inside the aws cloud deepcore starts by pulling imagery from that 100 petabyte library the most current imagery that's needed to support the next step which is applying ai now when we're talking about the volumes of data that we store in aws there's no possible way to use humans to do all the work and that's the reason why we use a set of trained ai models to extract various information layers those models are for things like roads or buildings or solar panels or any of a number of other objects that you might want to recognize in the imagery we label meaning we create the things that the model recognizes we label the imagery store that in rds and then we use the crowd to perform two functions one of them is to train the model in the first place and the other is to score the resulting labels from the model as a way of improving the quality of the ai model and then updating the model inside s3 we also use bitbucket and jenkins as a way of continuously deploying the code into the deep core architecture so after the windstorm passed through the day after we collected post-event satellite imagery of the same areas and then overlaid that with the information layers that we had extracted from the pre-event the most up-to-date pre-event imagery providing things like roads and building footprints that were then ingested into the applications that the first responders were using to find safe routes and to find a way to damage structures to evacuate or otherwise provide necessary services well it's a windstorm and one of the questions is where's that windstorm going to hit well maxar has been working in the weather domain as well the noaa supercomputer currently generates forecasts in about 100 minutes and it does that four times a day at the top of the hour well we decided to take that and put that in aws and tune the model and we were able to deliver that 58 faster saving basically an hour in the amount of time that it takes to generate the forecast well when a storm track is moving along the ground storm track changes and so having that forecast an hour ahead of time means an hour extra time to prepare to board up the windows to plan an evacuation or to hunt down the pet that decided to hide the worst possible time now the way that we do that in aws you see here on this chart and the benefit of working in aws is not only do we get performance but we get resiliency it operates in a number of availability zones so that we're not reliant on a single location and it's also able to scale up and scale down so we only run the model when we need to instead of having a data center that's operating 24 7 and not needed the net result of running this i mentioned 58 less compute time basically an hour faster than the noaa model for much less cost than the noaa supercomputer again because of that scalability we generated the same forecast quality as the high performance models from noaa and we believe it's applicable to other weather models in the where the process of updating it to support other weather models more on that in a moment so by being able to deliver the forecast 58 faster that opens up the possibility of running the forecast more times per day and i'll talk about how that's applicable in a moment well the world is a really big place and so one of the core questions that maxar has to address is where do we take the pictures well there are some things that help us but the most frequent change occurs where most people live and you can see in this map that there's a high correlation between population density and the density of change on the surface of the earth the world's population is concentrated about eight percent of the land is considered populated more than half the population lives on less than one percent of the land in densely populated urban areas about 95 of the population lives south of 50 degrees latitude and what maxar finds is about five percent of the land drives about 95 percent of our revenue so figuring out where in that really big planet to take pictures is a pretty important job for us and we have some sophisticated algorithms we use to do that optimization but it's also important to figure out when to take the pictures for example if it's cloudy there's not a lot of use in looking at the ground because the cloud obscures everything well after hurricane laura hit here are six image strips that were taken by our maxar satellites in the day after the hurricane hit and you can see that the only areas that are cloud-free are the ones that are outlined in purple so having an up-to-date weather forecast at the last possible minute would have allowed us to be more efficient in the way that we used our satellites and also use less storage storing data that is otherwise not usable and we're in the process of taking our our weather forecasting model and using it for precise of that purpose what you're seeing is all of those aspects that i talked about are living in the aws environment as maxar is all in on aws and whether that's the ingest of data both from our own satellites or other sources the weather forecasting the digital globe deep core to extract a variety of information layers supporting the crowd all of this running over and over continuously inside the aws environment well let me bridge to another example many of you have been following the wildfires that have been devastating communities in the western united states well one of the problems with wildfire is where there's fire there's smoke but fortunately maxar has the only commercial satellite that's able to see through the smoke worldview 3 to be able to identify where the fire lines are where burn structures are and to provide that to first responders and communities which we do via the open data program stored on aws well let's talk about another aspect of satellites which is when do they collect their data now for the longest time earth observation satellites have generally collected in either the late morning or in the early afternoon i'm not going to get into the the reasons for that but it boils down to synchronizing the orbits with the rotation of the earth and the sun so that if you're taking an image at say 10 30 in the morning in new york and the satellite zips around the planet and 90 minutes later it's over chicago it's going to be more or less about the same time in chicago plus or minus well not everything happens at 10 30 in the morning or 1 30 in the afternoon wouldn't it be nice to be able to get looks throughout the day well of course if you have looks throughout the day you're going to need those weather forecasts to be done much more rapidly to be able to support those multiple looks well we're actually doing that we're building a set of satellites called worldview legion that will be joining the maxar constellation next year uh the first couple of launches will be happening next year for an initial block of six legions well in addition to forecasting faster with the ability to look at the ground so many more times per day you want to be able to get the data and the way earth observation satellites get data to the ground is they when they're in range of a ground station they use radio to downlink the data to the ground station and these shaded areas you can see are the areas of the ground stations that max our beams it satellites to well not everything's in range of the ground stations so we have to store data on the satellite and that can take time so adding more ground stations allows us to get the data to the ground faster and that's one of the ways we've been working with aws ground station as a way of getting more often the data to the ground faster how fast well actually we've been able to demonstrate from collection of imagery to being in the s3 in an s3 bucket in the cloud in less than a minute that's pretty fast well let's go to another planet i mentioned uh maxar supports a number of planetary missions one of them is we built the robot arm for nasa jpl's mars insight lander which you can see here in this artist artist view this is the robot arm in operation in the lab on earth and the robot arm is used to pick up some of the instruments that were taken off the body of the lander and then placed onto the martian soil to perform a variety of measurements well one of those instruments which you can see in this next picture is the one that you see on the right uh it's a mole digger and it was designed to dig under the soil on the martian surface to go make measurements below the surface but if you were following the story around the insight lander there was a problem the mole essentially couldn't get a grip it was spinning around it wasn't able to grab on and dig the way that it was designed to do so the very smart engineers at nasa jpl came up with an idea which was to use the maxar robot arm to do something it wasn't designed to do they put the scoop on the robot arm and stuck it on top of the mold pushed them all into the martian soil so that the martian soil was able to or the mold digger was able to grab onto the soil and dig to do its job first case of interplanetary whack-a-mole as far as i'm aware let's come back closer to the ground or closer to earth i mentioned that maxar builds communication satellites and you can see a couple of them here those satellites sit out 25 000 miles above the ground so to be able to make those satellites work they need a lot of power to get that signal all the way down to the ground well we've used that technology to support a nasa mission called the lunar gateway that's a space station that orbits the moon that can move from place to place because it's used as a staging point for astronauts on their way to do various missions to the surface of the moon it's powered by very large solar arrays the same kinds that we use for our communication satellites and it uses a propulsion technology called electric propulsion and it's one that maxar has been a leader in for a number of years those are those really cool blue exhaust lines you see coming out of the back well what's important about electric propulsion is it it gets a lot more gas mileage it basically gets 10 more times as much gas mileage as you could get from chemical fuels so you go farther on a tank of gas of course what happens when you run out of gas well we're actually working on that too there's a mission we're doing for nasa osm1 and spyder and that is to go up grab onto a satellite refuel the satellite in space and release the satellite the other thing we're doing on the same mission is demonstrating the ability for a satellite to use robotics to assemble itself in this case assembling a large reflector dish as a way of moving from having to launch satellites that could only fit inside a the fairing on a rocket the nose cone on a rocket to being able to build much bigger structures in space well i mentioned communication satellites and one of the satellites that we built is for the australian national broadcasting network uh skymuster2 and it was used to beam uh high-speed internet to roughly 400 000 australians scattered throughout the the interior of australia is a huge huge continent one of the things that it was used for is distance learning because many of the school children in remote communities wouldn't be able to effectively commute to go to school well obviously distance learning is something that we've become a lot more familiar with in the time of covid speaking of covid maxar has been supporting coveted relief efforts by releasing information satellite information and other data for covered relief responses in about 20 countries around the world as part of the open data program where we release the data using aws s3 i'll just pick a few examples in sierra leone here's the city of beau sierra leone uh we worked with the government of sierra leone and a number of other partners to support their coveted response efforts for example one of the partners is grid three the census data that sierra leone had before the covet outbreak was old and in managing an outbreak you need to know where the people are so grid three develop population estimates based on the most current maxar satellite information satellite imagery and used that to feed into the covered response efforts for the government and it all fed a web portal that the government used to provide information to its citizens as well as informing many of the mitigation strategies social distancing evacuation delivery of relief supplies there are a few other examples as well when philippines were hit by typhoon vongfong maxar open data was used to support the evacuation and relief efforts in a way that maintained social distancing in south africa maxar data was used to map informal settlements that data was used to then plan how to deal with an outbreak if one occurred and how to safely evacuate or deliver supplies to the people who were affected in malawi our open data program was used to match the location of mobile payments to structures to mitigate fraud in kenya which was experiencing a major locust outbreak the open data program was used while farmers were told to stay home to monitor food security remotely while maintaining social distancing and in bangladesh open data was used to support mapping of dense urban areas to support government efforts at contract contact tracing so these are just a few of the many examples of how maxar and aws work together for a better world thank you wow thank you walter that was really an incredible discussion and it really does show that maxar is applying the cloud in space i wanted to finish up with a couple of key takeaways for everybody to just show you and discuss how aws really is offering a cloud that offers significant value to the space enterprises and their data as you can see several examples in that neat discussion we're offering scalable mission data processing so that you can actually ramp up the capacity that you need to support your space mission and then take it back down so that you're only paying for what you need and then also you saw an incredible use of data analytics in storage where that date is not just sitting there it's not just waiting for somebody to come look it up again the data's being used every second of the day to analyze predict estimate and do great things to help the world and then finally that leads into machine learning and artificial intelligence they're doing fantastic things using that ai and ml to help them find buildings help them show where disasters are causing problems helping to predict where uh people and populations are for coveted purposes and help people and that all comes from satellite products and data dissemination being used on the cloud with services when you need it where you need it around the world so those are the key takeaways that's showing you how aws and our new aerospace and satellite solutions team is working hard with incredible customers like maxar technologies to do great things for the world thank you for coming today we really appreciate your time and uh hope you have a great rest of reinvent

2021-02-10

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