Azure Maps in Azure Government

Azure Maps in Azure Government

[MUSIC]>>Hi. This is Steve Michelotti of the Azure Government
Engineering Team. I’m joined here today
by Chris Pendleton, Principal PM Manager of the
Azure Maps Team. Welcome Chris.>>Thank you.>>So we’re here to talk about
Azure Maps on Azure Government. Everyone knows what a Map is, but why don’t you start
out by just helping us understand what is Azure
Maps specifically.>>Yeah. So Azure Maps is the now government platform for mapping at Microsoft
inside the Azure Cloud. So what we did was, we basically stood up instances of of our Map
stacks in partnership with a number of companies and brought mapping capabilities to
the Azure Cloud natively. So now we’re running the services
natively in the Azure Cloud, and what we wanted to do was extend those capabilities to our
government customers. Now what we have is a super robust
set of location-based services running natively in the Azure Cloud for our government customers to use.>>So not only are
these native in Azure, you’re getting the power of
the Cloud but you already have an Azure government subscription
easy to provision Azure Maps.>>Exactly. You can just log
into the Azure portal for government and spin up an Azure
Maps account instantaneously.>>All right. Awesome. All
right, so what else we got here?>>Right. So Azure Maps is a very
robust suite of capabilities. Maps of course are natively
inherent in the mapping platform. We spent quite a bit
of time investing in the vector geometry
that goes into the Map. So it’s super, super robust. We also have satellite imagery
included as a part of Azure Maps, and that’s all actuated
through a set of SDKs. So today we have our
Web SDK that pulls down all that vector data and renders it into a map
as well as the imagery. Then all of the services actually
come to life in the SDK. So when you want to connect to
any of the Azure Map Services, you could do that through
our Azure Maps SDKs. The Azure Maps SDKs actually have quite a bit of robust
capabilities as well. So when you want to render push pins or points, you
want to render lines. You want to render polygons. You want to render
multiple layers of data, multiple layers of polygons, intersecting polygons, raster images. All of that actually is natively
included as capabilities in the Azure Maps Web SDK
as well as the Android SDK.>>Okay.>>So when we get into
some of the functionality, you’re going to find
that it’s quite robust. So if I move on to the
routing service for example, our route service has
multiple algorithms. You can request a route from A to B. You can request a route from A to N, meeting multiple
points along a route. We’ll even do route
optimization for you. So if you have a number of stops, you’re not sure what order
in which to do that. You submit those to us and we’ll actually do the
calculations for you. We have truck routing
attributes included as a part of the route
service as well. Then for some of the more advanced
algorithms like isochrones. So isochrones is basically I am here, where can I get to in one minute, two minutes, five minutes, 10 minutes in all directions. That ends up being a polygon
and from that polygon, you can then filter information for the things that you can
do within that polygon. As an example, I wanted to dive into some of the
routing capabilities, actually because it is the tip
of the iceberg if you will. So if you look at some
of these capabilities, we will do algorithms
for the fastest route or the shortest route which
is not always the same thing. You can have fuel efficient routes, thrilling routes. All
of these are built in. You can set a departure time
that you have to leave at, or an arrival time which means
if traffic conditions change, we’ll actually provide notifications
to you if you say have to be a catch plane for example and
there’s an accident all of a sudden. We also have pedestrian routing. So pedestrian, you want to include that into your
route calculation. That’s natively included
in the service as well. I mentioned truck routing
but truck routing is a very deep area when
it comes to routing. There’s quite a bit of
attributes that go into that. So for Azure Maps, we support a maximum
speed of a truck, the weight of a truck, the axle weight, the vehicle length. These are all attributes
that you pass in, and we’ll calculate the
best route for trucks. So that’s unique from vehicles
and its unique from bicycles. We also have bike routing
as well pedestrian route. These are very different
parameters that you need to use in order to calculate
routes specific for truck route.>>Right. Yeah, it’s interesting
as I saw the last slide, you had where it was just the icons. I saw icon for routing and you
think, okay, it’s directions. But then when you see a
slide like this and you say, it’s not just directions. There’s a lot more that goes into it. It’s really mind-boggling
how many variations and how efficient you can get with some of these
precise calculations. Interesting to see that.>>Yeah. My icon slide is a bit of a cheat slide because there’s so much under the covers there that come with this and you’re
seeing some of them now. Just being able to
avoid things and being able to use traffic in
your route calculations.>>Yeah.>>These are complex algorithms that we provide natively
as a part of that.>>Yeah. We peel back the layer on that one route icon on
this slide but I imagine we could probably do
that for every one of those icons if we had all the time.>>Absolutely.>>Okay.>>Yeah. Moving on to search. That’s another example. So I did want to mention. We have this very deep
partnership with TomTom, a company out of Netherlands. As a part of our
partnership with TomTom, they’re providing these
services under the covers. So what that means is, as a part of say the
search service we have access to every
piece of information that TomTom has ever
collected and made searchable in their APIs
through Azure Maps.>>Oh wow.>>So that means every address, every landmark, every place. These are also reversible,
so if you have a coordinate, I’ll tell you what
intersection you’re at, what address that’s at. So these can be done
in batches as well. So you look at some of the under the covers are tip of
the iceberg things for search. Same thing where you’ve got a ton
of capabilities, a ton of data, and a ton of different ways in
which you can filter that data when you’re trying to get to the point
of what you’re looking for.>>Right.>>You can actually filter down to exactly what you’re looking for.>>Okay. Cool. All
right. Let’s keep going.>>Yeah. We introduce
spatial operations as well. So spatial operations is two things. One is spatial calculations, so being able to analyze data, maybe if you’ve got a point and you’ve got a
number of other points, you want to know what’s the
closest to that isolated point.>>Yeah.>>These are great calculates.
We have Haversine calculations because as it turns out
the Earth is round. Some people don’t
believe that but it is. So we calculate for that. We also have a Geofencing Service built into our spatial operations. The Geofencing Service allows
our customers to upload fences or invisible
geometry into the Cloud, and then pin that
service with GPS points to know is this point in that fence, and then create a series of
alerts as a result of that. So the Geofencing Services
is super well received in the enterprise and
highly applicable in government when you want
to know where things are, and where they’re not, and when they should be there. So there’s a time aspect
for Geofence Service.>>Yeah. Just logistics
aspects alone. That’s huge. Logistics, so many aspects of our
government are based on that. That is as huge area, and that’s another
example where Maps isn’t just about seeing Maps or
knowing driving directions. It’s really about the precise
decision-making you can get with using all these
additional built-in services.>>Absolutely. I got a demo of that, so we’ll take a deeper look at that.>>Cool.>>We have a traffic service. So all the traffic flow for
dozens and dozens of countries around the world where you’ve got street-level information for the flow information
all the incidents. So traffic accidents, events, construction, all that fits
through into the traffic API. We’re seeing a lot of uptake in the traffic API for
smart city initiatives where you want to just be able to track that flow of traffic
through your city. There’s a lot of cities
that are struggling to just understand how traffic
flows through their system.>>Right.>>So a traffic service
like this where you’re getting massive amounts of information from different devices that amalgamate into a traffic flow, and being able to calculate the time it takes across
different states.>>The ones for governments, the
ones that do have those cities that need to understand traffic
patterns better. Perfect example.>>Exactly. We have a time zone API. So pass this coordinate, we’ll tell you what time zone it is, we’ll tell you what time it is there, we’ll tell you the offset to GMT, and we will tell you sunrise
and sunset at that location.>>Okay.>>This is critical
for IoT applications for lighting and
energy savings things.>>Right.>>We have a Geolocation API. You pass this in IP address, we’ll tell you what country that
calls coming from that helps you customize experiences to your customers localization
things like that. We have a mobility service. Mobility service is
basically public transit. All right? So you want to
find the nearest bus stop. You want to find the
nearest train station. It also provides
real-time information for a number of municipalities. Where is the bus? Where is the train in real time?>>Okay,.>>We partnered with a company
called Moovit to build out our mobility service. So under the covers, we’re getting actually billions of input from crowdsourced
information that feeds into this Moovit platform that we then surface through Azure Maps and make it available
to both our customers.>>Cool.>>Then we have a data
storage service as well. This is largely the backend
of our geofencing API. So when you want to store geofences in the Azure
Maps part of the Cloud, it will just go into
the data storage. We recently announced “Weather”, So weather service and this provides real time
information of weather, you can see radar,
you can see infrared, there’s overlays on the
map but you can also see weather information
for current conditions. You’ll be able to see
the future forecasts for different areas and then we will
have a weather along a route. So given a particular route, you’ll know what the weather
is for a certain amount of time as you’re driving
that route and so->>Just being able to get all
of those in one subscription, one Cloud provider
and not have to have 50 different licenses or subscriptions,
the different customers. I mean, just being
able to have all of that integrated in one solution is just a huge efficiency
timesaver if nothing else.>>It really is. I should mention our weather service
is powered by AccuWeather, the best weather company. They’ve won multiple
awards to prove that. We surface their weather because weather becomes a
significant signal for a number of scenarios ranging from agriculture to automotive,
and transport. So weather is a critical
aspect and yeah, you don’t have to negotiate with TomTom and Moovit, and AccuWeather.>>AccuWeather, yeah.>>Azure maps. We bring all these
Azure Maps capabilities as well, you just need an Azure
Map subscription.>>Awesome.>>Yeah.>>Great.>>Then I should mention we also announced integration with Power BI. So for Power BI, customers
that use Power BI, Azure Maps is there as well.>>Great. Let’s keep going.>>Great. So let’s go into some of
the applications of Azure Maps. We sit inside of the
Azure IoT organization and so when I think
about maps and location, I think about IoT. Inside of Azure IoT, we actually think about three aspects of the evolution of
installing devices. So one is the device
sensors themselves, those device sensors emit
a ton of information. Whether it’s temperature or
humidity, whatever it is, they’re emitting all of this data
out so that you as a customer, can make data-driven decisions. So that data is pumping up into Azure and you’re making
these data-driven decisions, that’s great, we bring
a filter of location. So not only are you seeing devices that are producing information
and you’re making decisions, we filter that out so you know
where to make those decisions, you know where those devices
are in the real world and you can apply a filter of
location on top of your IoT data. We call that the location of things. It’s a great concept because it does intersect location in the IoT world.>>Yet another example of having everything cohesively work
together in the Cloud.>>Exactly right. That’s right. So this is a sample of
vehicle telemetry coming in, this will feed into a demo. So this vehicle telemetry
comes up in through “IoT Hub”. So Azure IoT has IoT Hub which
basically receives messages. We’ll take those messages and send
it over to Event Grid to check. This particular demo or
this particular stack, we’ll actually walk through what
it’s like to track a vehicle. So what we want to do
is if this vehicle has left the geofence, send an alert. So the stack when you walk through, this telemetry is coming in, IoT is taking it in and
submitting it back, we’ll check it with the Event Grid. Event Grid is actually calling an Azure function that
calls Azure Maps, and Azure Maps is
checking is this GPS coordinate in the geofence or not. So you’ll get the constant reading, it’s in, it’s in, it’s in, and as soon as it goes out, you get a cascade of events that
you as a customer can control. These could be alerts, these could be text
messages, e-mails. These could be other cascading
events, notifications to others. This could be reroute other things, determine the directionality.
Things like this.>>So this vehicle could be a
police car, could be a Humvee. Anything that we integrate
with IoT Hub, we can track.>>Exactly right.>>Cool.>>That’s right.>>Good. So I wanted
to demonstrate this because we are seeing vehicles getting connected
more and more every day, and where those vehicles
are actually matters. So I think in government scenarios, it’s important to understand not just where they are
but where they aren’t, and where they should be, and that’s where this geofencing
demo can come in pretty handy. But you can also think of scenarios where you just want to
know when they’re close, you’re tracking a particular vehicle and you want to know
when they’re close. So let me demonstrate
geofencing in this context. So what I’ve got here is
a sample application, I’ve set Bethesda as an origin, I’ve got the White
House as a destination. I’ve got a radius of the
geofence here, three kilometers. I’m just going to hit “Play” and
what this does is it ends up calculating a route from
Bethesda to the White House. It’s going to animate the
telemetry of a vehicle. So this is a simulation
if you will where we took the route geometry
that was created by the route service and pushed it back, and now we’re just tracing through. This is a car driving through, and as it approaches the geofence, you’ll see boom, it
kicks off an alert. I have now entered the fence. So this could cascade
into a number of events and then once it
arrives at the destination, another alert kicks off.>>Okay. I saw you had a
three-kilometer radius, I’m presuming you can configure that?>>Absolutely. So the three
kilometers, totally arbitrary. It could be a circle, it could be a bigger circle, it
could be a polygon.>>Wow.>>We see a lot of routing scenarios. So like if a truck leaves a route, an alert kicks off
because I want to know, this is great in shipping
scenarios as well. So this result geometry based and so it doesn’t matter that it’s over
the ocean or over land. So this could be a shipping
container or an actual ship, vessel that is
traversing over the seas and if it leaves a
projected trajectory, we can actually get a notification, maybe there’s something going on.>>Okay, cool. All
right, what’s next?>>Yeah, so I wanted to
actually cover some of the compliance factors that went into shipping Azure Maps
in the government Cloud. This is an important factor and
it’s actually not easy to achieve, but we are fully Cloud-scale. So when we talk about Cloud ready, we’re talking about Cloud scale, we’re talking about
global availability, we’re talking about
a web and mobile SDK fully integrated with other
Azure services as well. So when you come to Azure and you
want to use Azure capabilities, Azure Maps is probably integrated
to other services as well. Then trusted security services, this is all the
compliance factors that actually feed in not just security, but we are fully security
compliant when it comes to Azure. We have Azure Active
Directory Tenancy as well. GDPR compliance. So when customers want
to check that box, it’s important we are
fully compliant with GDPR. Then for accessibility,
usability, globalization, these are all factors
to ship in Azure, and they are a little more stringent when it comes to the
government Cloud. I should say that the
Azure Maps Web SDK actually got a grade
B for accessibility. It’s only the ninth
product to ever do that. So we’re pretty proud of that, and wanted to make sure
that that was aware, that accessibility is an
important feature for us as well.>>Great. All right.>>Cool. The other thing
I wanted to talk about is the code sample site.>>Okay.>>So first of all, mapping these services
can get a little complex, and so we’ve built
a site dedicated to government customers who want
to code against Azure Maps.>>Great.>>So what I’ll go through
is a few of these demos, but I did want to at least flag the fact that this site is out there for government developers who
are starting to integrate this, and for business decision-makers
who don’t know how to code. So our enterprise customers
have enjoyed some of the fruits of our labor when it
comes to these code samples, and there’s 160 plus code samples that have been available to them, but now we’ve ported that
over to the GovCloud. So you’ll notice that is hosted on the GovCloud.>>So anyone can go to that. Any customer can go to that URL right now and see
the samples themselves.>>Absolutely.>>Cool.>>What’s beautiful about that is it’s made for business
decision-makers, as well as developers.>>Great.>>So if you are a
business decision-maker, you can come in and check out some of the functionality that is inherent
in the Azure Maps platform. As a developer, you can come and see the functionality
and get the code. So we have all of this
code running in GitHub. You can go to GitHub, it’s
freely open available, and you can just grab it and start running with it with
your Azure Maps key.>>Okay. So let’s look
at a couple of samples.>>Yes. Absolutely. So first I’ll demo a drag and drop GeoJSON
sample that we have. So this uses Azure Maps, under the covers of course,
and this is our Web SDK. You can go to to get a bunch of just open-source datasets. So linking over here, I can go over and download
a bunch of different sets. I went ahead and downloaded
some ahead of time. So what I want to do is
basically grab one of these. This 2016 election results
voter turnout for Virginia. I’m going to drag this over to the map and just drop
it right on there. You’ll see that it just renders
natively right onto the map.>>Wow. Okay. You just do
that right from>>Right from There is a lot, so when
you see this GeoJSON icon, all of these are
available for download. Grab them, download
them, and just drag it on to Azure Maps.
It’ll just render.>>Awesome. Okay.>>Yeah. Then, of course, from there you can
jump over to GitHub, and source code for that specific
demo is available right there.>>Okay. So any of the demos, I’ll have the source code
button I can jump over as a developer and
look at how to do it.>>Absolutely.>>Okay.>>Yeah.>>All right. What’s next?>>Great. So let’s
move on to heat maps. So the heat maps have
some super visual impact. When you want to look at data and
you want to see it aggregated, we could just jump into
this sample, for example. What this does is it keeps the size of the data consistent
as you zoom in and out. So as I’m zooming out, you’ll see that it
doesn’t grow with me. It’s actually staying the absolute
size that it needs to be, relative to the map zoom level.>>All right. Even as
you’re zooming out, zooming in, as we go
through these samples, like just the visual
aesthetics on these, and just the high-fidelity of visuals I’m seeing,
it’s pretty amazing.>>Yeah. We spent a lot of
time designing Azure maps. In fact, and not to mention, all of the data coming through
in the map itself is vector. So we don’t have any
REST aspects of this. This is all tiles. It’s all vector data
pumped into tiles, and so we’re able to control design
and rendering on the client, which allows us to get super sharp edges and
super crisp rendering.>>Much higher fidelity. Okay. Cool.>>Yeah. So this, basically you pull in data, we’ll create a heat map
for you as an overlay. You can set the translucence
and zoom in and out. Again, we separated the
layers of the map as well. So that as you’re
pulling your data in, you don’t lose the labels. This is actually an
important thing that a lot of competitors actually
struggle with, and they actually put data on top and you lose all the
underlying context. So what we did is we separated
the labels layer and now you can render your
data under the labels, but still on top of the map.>>Okay.>>Cool.>>Yeah. Let’s see another one.>>Yeah. So next one I want to
show is a convex hull and markers. What this actually illustrates
is a couple of things. One, you can put data on
top of the map absolutely, but then you can control it. So what you’re able to
do is grab these pins, and at runtime, I’m basically
changing the polygons. So these pins can control the
extents of this particular shape. But also, I’m getting events
listening into the client. So what that means is I’m
actually getting the coordinates, but I’m also getting the pixel count, and it converts to measurements. So now I can measure the actual perimeter of
this particular shape, and I can move these
around and try to pull this into a concave hull. But it also measures the area. So as I’m manipulating
the data on the map, which is fully flexible, I can actually do calculations
on top of that as well.>>I can just drag and drop around, and I don’t have to do all
the math myself in advance.>>Took care that for you.>>Okay. Great.>>That’s right. So the last demo I wanted to show you is our weather. So I mentioned we recently
announced our weather service. So I’m going to click over
to this particular demo. What you’ll see here is our map. By the way, we do have
multiple styles of the map. So our normal cartographic map
which you’re commenting on. We also have a dark, we have a night, we have a couple of grays. But what it does is it
makes your data pop.>>Yeah.>>So if you look at this
weather information, that’s overlaying on top, this is radar information
overlaying on top of the Azure Map. I’m going to zoom out so you can
see it’s data for the world.>>Yeah.>>So we’re getting all
of this data globally. We also have infrared
information as well. So you can get heat signatures
rendered on top of the map.>>Okay.>>Select that. There we go.>>Oh, wow. There’s the
infrared right there.>>So there’s infrared coming in. Yeah. Again, fully scales with
the map comes as another layer, and your labels stay on top.>>Okay. Great. So in addition to
of course regular documentation, probably the area to get
started is this website right here, the So this has been Steve Michelotti
with Chris Pendleton talking about Azure Maps on Azure
Government. Thanks for watching. [MUSIC]

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