Hello, welcome to 'This is My Architecture.'
Today we are with Mikel Coira Murga,
who is Head of Artificial Intelligence Platforms
at Telefónica Tech AI of Things.
-Welcome, Mikel. -Thank you so much.
It's a pleasure being here.
What exactly do you do
at Telefónica Tech AI of Things?
Well, it's the union of our areas,
the internet of things and artificial intelligence,
to be able to take a combined proposal to clients.
Today we're going to talk about one of your solutions,
called AI Suite.
What is AI Suite?
Well, despite what we constantly see in the media,
that businesses should use artificial intelligence,
the reality is that most don't have the equipment
or the training to be able to use
machine learning models.
Plus, their business areas can't exploit them.
Those two problems are the ones AI Suite can solve.
Let's go deeper into the architecture.
How have you evolved over the last few years?
Well, AI Suite started as a group of libraries
and tools to accelerate our
data consultation projects, right?
And little by little
it has evolved into a platform.
And that's the time to start to simplify
our operations,
and accelerate our developments through
the adoption of self-managed services from AWS.
Very interesting.
How have you been able to scale that architecture
to be able to manage all those user accounts,
those user environments?
Well, our clients
deposit their most valuable
asset in our accounts, which is the data,
and what we do is, within our organization,
we create an AWS account for each user.
The way to supply those accounts is via
the Service Catalog.
But of course, as these accounts
increase, we need
to be able to manage them.
And that's where the Control Tower comes into play.
Plus, it allows us to establish the security guides
through guardrails.
How are you able to scale and at the same time,
preserve the security of the information
for each one of your clients?
Well, in addition to assigning the account,
later, when a client stores information, they do it
in an S3 bucket, which is assigned,
and that information is encrypted to REST.
Plus, everything having to do with
data processing is done
in infrastructures that are created each time
that the client executes a task,
built according to the size
of the data that will be used.
Very interesting. You talked about services
that are built for each account,
for each client, and here we see AWS Glue and Amazon
and EMR.
How do they complement each other?
When do you use each one of them?
We have a very large a database of codes
from the onset,
and we have the experience of executing
tasks in EMR, right?
What happens, since we already said we are undergoing
an evolution toward self-managed services,
so everything having to do with transformation
of datasets and data profiling,
we're moving that to Glue.
And I understand that this whole environment of accounts will be complemented
with a backend within your architecture.
What architecture do you have for that layer?
That being, our system's backend
is an application in a node that we put into
a container.
So, ECS is the perfect companion
to be able to deploy those containers
without having to worry
about managing the machines,
plus, when we incorporate an Application Load Balancer,
we can make this elastic
and we can provide service to all the requests that enter.
Perfect. And from that backend,
what types of data storage service
do you use to preserve that information?
Well, we talked about our groups
of raw and transformed data
in an S3, however,
there is much more information, like statistics on that data,
the algorithms and hyperparameters
that we have used to train,
or even the user information.
All that information is stored in DocumentDB,
which is in JSON format, being very flexible, providing us
the agility we want for development.
On the other hand, we finally have a bunch of deployed containers,
and on certain occasions we need to coordinate them.
In that case we use the native characteristics
of Redis, in this case, to create
publication-subscription queues,
and their native integration with Socket.IO.
This vision of AI Suite is very interesting.
How do you plan to evolve the architecture in the future?
We have three open fronts.
The first is to keep migrating to
self-managed services, so, for example,
all the user management, we want to take to Cognito,
all the data transformation, we want to take to DataBrew.
But there's another front, which is how to keep increasing
the functionality of the platform,
enriching the models with data.
That's where Redshift Spectrum or Athena
come into play, for example.
And lastly, we also want to grow
the business and reach more clients,
and for that we are using AWS Marketplace.
Thank you, Mikel, for sharing your
AI Suite experiences with us.
Thank you.
And thank you to everyone for joining
'This is My Architecture.'