Welcome to "This is My Architecture," I'm Lana from AWS,
and today we're talking to Santhosh from Mahindra Electric.
Welcome.
Hi, Lana, great to be here.
Awesome having you here, could you tell us more about Mahindra Electric?
Absolutely.
Mahindra Electric is part of the $21 billion dollar Mahindra group
We are actually the pioneers in electric vehicle technology and sustainable transportation in India.
So we design, develop and manufacture all the components of an electric vehicle.
At the same time,
we actually have mobility solutions, as one of the key pillars of our business strategy.
So we have a platform called NEMO, which stands for next generation mobility,
through which we offer connected shared and electric services to our customers.
And the entire platform is hosted on AWS.
Great.
Let's dive in, So I'm seeing here an electric vehicle.
So how does it communicate to the platform?
Yeah, look,
we have electric vehicles, which is actually three wheels as well as four wheels,
in our portfolio today. All of these electric vehicles actually share a lot of data,
or push a lot of data to Cloud and the starting point is Load Balancer.
This goes over MQTT, or TCP IP, and various of the protocols that we are actually enabling.
And this is where the Load Balancer takes the data and pushes it to the Broker and finally to Kinesis.
Got it.
So we have a Broker running on EC2 instance, that later on pushes data into a Kinesis stream?
That's correct, and, for us,
I think in the whole architecture, data reliability is actually the key.
So we actually stored the data at least for three days in Kinesis.
And we do a lot of processing of the data, which is in Kinesis.
And there are two kinds of processing that we actually do.
So one, for example, if you have vehicle alerts coming into Kinesis,
we actually have Lambda picking up the data,
and in this case,
let's say a geo-sensing alert came from the vehicle and because the vehicle moved out of a particular area,
and that has to be notified all the way to the fleet operator immediately.
So in that case, the Lamda, picks up that event, sends it to SNS and finally to the fleet operator
who's sitting and monitoring the fleets here.
At the same time, the rest of the data, which is coming in from Kinesis goes through the Lamda.
>> And finally gets stored in S3. >> Great.
So not only do we take actions that need to be taken in a time sensitive manner but,
we can also analyze the rest of the data that is flowing into the S3 bucket.
So this is looking to me like a pretty great data lake. Is that how you're using S3 and Athena services?
Exactly.
You know, we use S3 as the single source of truth for all our data scientists.
In fact, just to give you a scale,
we actually have around 175 million e-kilometers of data and that's terabytes of data being stored in S3 today.
And would you mind telling us what e-kilometers are?
Absolutely,
You know, the fact that the whole architecture is is actually for electric vehicles,
we are talking about electric kilometres done from this architecture
and then all of those data is actually stored in S3
So we have terabytes and terabytes of data in S3,
so how are we using Glue to catalog and organize this data?
Look, we need to extract a lot of intelligence coming from the data because the data includes
battery related data, you know, data on charging and so on.
So Glue, is actually used to scan the data, curate the data and do transformations on the data,
and we store it back into S3 in this case.
So basically, let me take an example here.
In the case of for our fleet operators,
we provide something called driver rating for each of the drivers.
And, in that case, a driver rating algorithm is running and the Glue picks up the relevant data,
creates a driver rating report and puts it back into S3.
And finally, all of this data is actually sent using Athena back to our fleet operators,
using a variety of insights given through dashboards,
- So this way our fleet operators have a single pane of glass
to see the immediate alerts they have to take action on
and also some of the insights on driver's performance,
better data, et cetera, et cetera.
Absolutely.
And they have all of this at their fingertips,
which helps them improve their fleet utilization and improve their operations.
Great.
Santhosh, thank you so much for coming today and telling us about Mahindra Electric.
>> And the platform you've built on AWS. >> Thank you so much.
And thank you for watching, "This is My Architecture."